An Approach to Remove the Systematic Bias from the Storm Surge forecasts in the Venice Lagoon

Science.gov (United States)

Canestrelli, A.

2017-12-01

In this work a novel approach is proposed for removing the systematic bias from the storm surge forecast computed by a two-dimensional shallow-water model. The model covers both the Adriatic and Mediterranean seas and provides the forecast at the entrance of the Venice Lagoon. The wind drag coefficient at the water-air interface is treated as a calibration parameter, with a different value for each range of wind velocities and wind directions. This sums up to a total of 16-64 parameters to be calibrated, depending on the chosen resolution. The best set of parameters is determined by means of an optimization procedure, which minimizes the RMS error between measured and modeled water level in Venice for the period 2011-2015. It is shown that a bias is present, for which the peaks of wind velocities provided by the weather forecast are largely underestimated, and that the calibration procedure removes this bias. When the calibrated model is used to reproduce events not included in the calibration dataset, the forecast error is strongly reduced, thus confirming the quality of our procedure. The proposed approach it is not site-specific and could be applied to different situations, such as storm surges caused by intense hurricanes.

Use of GPS TEC Maps for Calibrating Single Band VLBI Sessions

Science.gov (United States)

Gordon, David

2010-01-01

GPS TEC ionosphere maps were first applied to a series of K and Q band VLBA astrometry sessions to try to eliminate a declination bias in estimated source positions. Their usage has been expanded to calibrate X-band only VLBI observations as well. At K-band, approx.60% of the declination bias appears to be removed with the application of GPS ionosphere calibrations. At X-band however, it appears that up to 90% or more of the declination bias is removed, with a corresponding increase in RA and declination uncertainties of approx.0.5 mas. GPS ionosphere calibrations may be very useful for improving the estimated positions of the X-only and S-only sources in the VCS and RDV sessions.

A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield.

Science.gov (United States)

Ringard, Justine; Seyler, Frederique; Linguet, Laurent

2017-06-16

Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale.

The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

Science.gov (United States)

Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2018-01-01

Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

An integrated pan-tropical biomass map using multiple reference datasets

OpenAIRE

Avitabile, V.; Herold, M.; Heuvelink, G. B. M.; Lewis, S. L.; Phillips, O. L.; Asner, G. P.; Armston, J.; Ashton, P. S.; Banin, L.; Bayol, N.; Berry, N. J.; Boeckx, P.; de Jong, B. H. J.; DeVries, B.; Girardin, C. A. J.

2016-01-01

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging...

Lensing reconstruction from a patchwork of polarization maps

International Nuclear Information System (INIS)

Namikawa, Toshiya; Nagata, Ryo

2014-01-01

The lensing signals involved in CMB polarization maps have already been measured with ground-based experiments such as SPTpol and POLARBEAR, and would become important as a probe of cosmological and astrophysical issues in the near future. Sizes of polarization maps from ground-based experiments are, however, limited by contamination of long wavelength modes of observational noise. To further extract the lensing signals, we explore feasibility of measuring lensing signals from a collection of small sky maps each of which is observed separately by a ground-based large telescope, i.e., lensing reconstruction from a patchwork map of large sky coverage organized from small sky patches. We show that, although the B-mode power spectrum obtained from the patchwork map is biased due to baseline uncertainty, bias on the lensing potential would be negligible if the B-mode on scales larger than the blowup scale of 1/f noise is removed in the lensing reconstruction. As examples of cosmological applications, we also show 1) the cross-correlations between the reconstructed lensing potential and full-sky temperature/polarization maps from satellite missions such as PLANCK and LiteBIRD, and 2) the use of the reconstructed potential for delensing B-mode polarization of LiteBIRD observation

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

Science.gov (United States)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin

Multiple Description Coding Based on Optimized Redundancy Removal for 3D Depth Map

Directory of Open Access Journals (Sweden)

Sen Han

2016-06-01

Full Text Available Multiple description (MD coding is a promising alternative for the robust transmission of information over error-prone channels. In 3D image technology, the depth map represents the distance between the camera and objects in the scene. Using the depth map combined with the existing multiview image, it can be efficient to synthesize images of any virtual viewpoint position, which can display more realistic 3D scenes. Differently from the conventional 2D texture image, the depth map contains a lot of spatial redundancy information, which is not necessary for view synthesis, but may result in the waste of compressed bits, especially when using MD coding for robust transmission. In this paper, we focus on the redundancy removal of MD coding based on the DCT (discrete cosine transform domain. In view of the characteristics of DCT coefficients, at the encoder, a Lagrange optimization approach is designed to determine the amounts of high frequency coefficients in the DCT domain to be removed. It is noted considering the low computing complexity that the entropy is adopted to estimate the bit rate in the optimization. Furthermore, at the decoder, adaptive zero-padding is applied to reconstruct the depth map when some information is lost. The experimental results have shown that compared to the corresponding scheme, the proposed method demonstrates better rate central and side distortion performance.

Fixed points of occasionally weakly biased mappings

OpenAIRE

Y. Mahendra Singh, M. R. Singh

2012-01-01

Common fixed point results due to Pant et al. [Pant et al., Weak reciprocal continuity and fixed point theorems, Ann Univ Ferrara, 57(1), 181-190 (2011)] are extended to a class of non commuting operators called occasionally weakly biased pair[ N. Hussain, M. A. Khamsi A. Latif, Commonfixed points for JH-operators and occasionally weakly biased pairs under relaxed conditions, Nonlinear Analysis, 74, 2133-2140 (2011)]. We also provideillustrative examples to justify the improvements. Abstract....

Removing Visual Bias in Filament Identification: A New Goodness-of-fit Measure

Science.gov (United States)

Green, C.-E.; Cunningham, M. R.; Dawson, J. R.; Jones, P. A.; Novak, G.; Fissel, L. M.

2017-05-01

Different combinations of input parameters to filament identification algorithms, such as disperse and filfinder, produce numerous different output skeletons. The skeletons are a one-pixel-wide representation of the filamentary structure in the original input image. However, these output skeletons may not necessarily be a good representation of that structure. Furthermore, a given skeleton may not be as good of a representation as another. Previously, there has been no mathematical “goodness-of-fit” measure to compare output skeletons to the input image. Thus far this has been assessed visually, introducing visual bias. We propose the application of the mean structural similarity index (MSSIM) as a mathematical goodness-of-fit measure. We describe the use of the MSSIM to find the output skeletons that are the most mathematically similar to the original input image (the optimum, or “best,” skeletons) for a given algorithm, and independently of the algorithm. This measure makes possible systematic parameter studies, aimed at finding the subset of input parameter values returning optimum skeletons. It can also be applied to the output of non-skeleton-based filament identification algorithms, such as the Hessian matrix method. The MSSIM removes the need to visually examine thousands of output skeletons, and eliminates the visual bias, subjectivity, and limited reproducibility inherent in that process, representing a major improvement upon existing techniques. Importantly, it also allows further automation in the post-processing of output skeletons, which is crucial in this era of “big data.”

Global Ionosphere Mapping and Differential Code Bias Estimation during Low and High Solar Activity Periods with GIMAS Software

Directory of Open Access Journals (Sweden)

Qiang Zhang

2018-05-01

Full Text Available Ionosphere research using the Global Navigation Satellite Systems (GNSS techniques is a hot topic, with their unprecedented high temporal and spatial sampling rate. We introduced a new GNSS Ionosphere Monitoring and Analysis Software (GIMAS in order to model the global ionosphere vertical total electron content (VTEC maps and to estimate the GPS and GLObalnaya NAvigatsionnaya Sputnikovaya Sistema (GLONASS satellite and receiver differential code biases (DCBs. The GIMAS-based Global Ionosphere Map (GIM products during low (day of year from 202 to 231, in 2008 and high (day of year from 050 to 079, in 2014 solar activity periods were investigated and assessed. The results showed that the biases of the GIMAS-based VTEC maps relative to the International GNSS Service (IGS Ionosphere Associate Analysis Centers (IAACs VTEC maps ranged from −3.0 to 1.0 TECU (TEC unit (1 TECU = 1 × 1016 electrons/m2. The standard deviations (STDs ranged from 0.7 to 1.9 TECU in 2008, and from 2.0 to 8.0 TECU in 2014. The STDs at a low latitude were significantly larger than those at middle and high latitudes, as a result of the ionospheric latitudinal gradients. When compared with the Jason-2 VTEC measurements, the GIMAS-based VTEC maps showed a negative systematic bias of about −1.8 TECU in 2008, and a positive systematic bias of about +2.2 TECU in 2014. The STDs were about 2.0 TECU in 2008, and ranged from 2.2 to 8.5 TECU in 2014. Furthermore, the aforementioned characteristics were strongly related to the conditions of the ionosphere variation and the geographic latitude. The GPS and GLONASS satellite and receiver P1-P2 DCBs were compared with the IAACs DCBs. The root mean squares (RMSs were 0.16–0.20 ns in 2008 and 0.13–0.25 ns in 2014 for the GPS satellites and 0.26–0.31 ns in 2014 for the GLONASS satellites. The RMSs of receiver DCBs were 0.21–0.42 ns in 2008 and 0.33–1.47 ns in 2014 for GPS and 0.67–0.96 ns in 2014 for GLONASS. The monthly

A hidden bias in a common calorimeter calibration scheme

International Nuclear Information System (INIS)

Lincoln, Don; Morrow, Greg; Kasper, Peter

1994-01-01

In this paper, a common calorimeter calibration scheme is explored and a hidden bias found. Since this bias mimics a non-linearity in response in the calorimeter, it must be understood and removed from the calibration before true non-linearities are investigated. The effect and its removal are explored and understood through straightforward calculus and algebra. ((orig.))

Removing non-urban roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011

Science.gov (United States)

Soulard, Christopher E.; Acevedo, William; Stehman, Stephen V.

2018-01-01

Quantifying change in urban land provides important information to create empirical models examining the effects of human land use. Maps of developed land from the National Land Cover Database (NLCD) of the conterminous United States include rural roads in the developed land class and therefore overestimate the amount of urban land. To better map the urban class and understand how urban lands change over time, we removed rural roads and small patches of rural development from the NLCD developed class and created four wall-to-wall maps (1992, 2001, 2006, and 2011) of urban land. Removing rural roads from the NLCD developed class involved a multi-step filtering process, data fusion using geospatial road and developed land data, and manual editing. Reference data classified as urban or not urban from a stratified random sample was used to assess the accuracy of the 2001 and 2006 urban and NLCD maps. The newly created urban maps had higher overall accuracy (98.7 percent) than the NLCD maps (96.2 percent). More importantly, the urban maps resulted in lower commission error of the urban class (23 percent versus 57 percent for the NLCD in 2006) with the trade-off of slightly inflated omission error (20 percent for the urban map, 16 percent for NLCD in 2006). The removal of approximately 230,000 km2 of rural roads from the NLCD developed class resulted in maps that better characterize the urban footprint. These urban maps are more suited to modeling applications and policy decisions that rely on quantitative and spatially explicit information regarding urban lands.

The refinement of ipsilateral eye retinotopic maps is increased by removing the dominant contralateral eye in adult mice.

Directory of Open Access Journals (Sweden)

Spencer L Smith

2010-03-01

Full Text Available Shortly after eye opening, initially disorganized visual cortex circuitry is rapidly refined to form smooth retinotopic maps. This process asymptotes long before adulthood, but it is unknown whether further refinement is possible. Prior work from our lab has shown that the retinotopic map of the non-dominant ipsilateral eye develops faster when the dominant contralateral eye is removed. We examined whether input from the contralateral eye might also limit the ultimate refinement of the ipsilateral eye retinotopic map in adults. In addition, we examined whether the increased refinement involved the recruitment of adjacent cortical area.By surgically implanting a chronic optical window over visual cortex in mice, we repeatedly measured the degree of retinotopic map refinement using quantitative intrinsic signal optical imaging over four weeks. We removed the contralateral eye and observed that the retinotopic map for the ipsilateral eye was further refined and the maximum magnitude of response increased. However, these changes were not accompanied by an increase in the area of responsive cortex.Since the retinotopic map was functionally refined to a greater degree without taking over adjacent cortical area, we conclude that input from the contralateral eye limits the normal refinement of visual cortical circuitry in mice. These findings suggest that the refinement capacity of cortical circuitry is normally saturated.

Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain

Science.gov (United States)

Fang, Jinsheng; Bao, Lijun; Li, Xu; van Zijl, Peter C. M.; Chen, Zhong

2017-08-01

Background field removal is an important MR phase preprocessing step for quantitative susceptibility mapping (QSM). It separates the local field induced by tissue magnetic susceptibility sources from the background field generated by sources outside a region of interest, e.g. brain, such as air-tissue interface. In the vicinity of air-tissue boundary, e.g. skull and paranasal sinuses, where large susceptibility variations exist, present background field removal methods are usually insufficient and these regions often need to be excluded by brain mask erosion at the expense of losing information of local field and thus susceptibility measures in these regions. In this paper, we propose an extension to the variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP) background field removal method using a region adaptive kernel (R-SHARP), in which a scalable spherical Gaussian kernel (SGK) is employed with its kernel radius and weights adjustable according to an energy "functional" reflecting the magnitude of field variation. Such an energy functional is defined in terms of a contour and two fitting functions incorporating regularization terms, from which a curve evolution model in level set formation is derived for energy minimization. We utilize it to detect regions of with a large field gradient caused by strong susceptibility variation. In such regions, the SGK will have a small radius and high weight at the sphere center in a manner adaptive to the voxel energy of the field perturbation. Using the proposed method, the background field generated from external sources can be effectively removed to get a more accurate estimation of the local field and thus of the QSM dipole inversion to map local tissue susceptibility sources. Numerical simulation, phantom and in vivo human brain data demonstrate improved performance of R-SHARP compared to V-SHARP and RESHARP (regularization enabled SHARP) methods, even when the whole paranasal sinus regions

An integrated pan-tropical biomass map using multiple reference datasets.

Science.gov (United States)

Avitabile, Valerio; Herold, Martin; Heuvelink, Gerard B M; Lewis, Simon L; Phillips, Oliver L; Asner, Gregory P; Armston, John; Ashton, Peter S; Banin, Lindsay; Bayol, Nicolas; Berry, Nicholas J; Boeckx, Pascal; de Jong, Bernardus H J; DeVries, Ben; Girardin, Cecile A J; Kearsley, Elizabeth; Lindsell, Jeremy A; Lopez-Gonzalez, Gabriela; Lucas, Richard; Malhi, Yadvinder; Morel, Alexandra; Mitchard, Edward T A; Nagy, Laszlo; Qie, Lan; Quinones, Marcela J; Ryan, Casey M; Ferry, Slik J W; Sunderland, Terry; Laurin, Gaia Vaglio; Gatti, Roberto Cazzolla; Valentini, Riccardo; Verbeeck, Hans; Wijaya, Arief; Willcock, Simon

2016-04-01

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets. © 2015 John Wiley & Sons Ltd.

Foreground removal from Planck Sky Model temperature maps using a MLP neural network

Science.gov (United States)

Nørgaard-Nielsen, H. U.; Hebert, K.

2009-08-01

Unfortunately, the Cosmic Microwave Background (CMB) radiation is contaminated by emission originating in the Milky Way (synchrotron, free-free and dust emission). Since the cosmological information is statistically in nature, it is essential to remove this foreground emission and leave the CMB with no systematic errors. To demonstrate the feasibility of a simple multilayer perceptron (MLP) neural network for extracting the CMB temperature signal, we have analyzed a specific data set, namely the Planck Sky Model maps, developed for evaluation of different component separation methods before including them in the Planck data analysis pipeline. It is found that a MLP neural network can provide a CMB map of about 80 % of the sky to a very high degree uncorrelated with the foreground components. Also the derived power spectrum shows little evidence for systematic errors.

Performance of non-parametric algorithms for spatial mapping of tropical forest structure

Directory of Open Access Journals (Sweden)

Liang Xu

2016-08-01

Full Text Available Abstract Background Mapping tropical forest structure is a critical requirement for accurate estimation of emissions and removals from land use activities. With the availability of a wide range of remote sensing imagery of vegetation characteristics from space, development of finer resolution and more accurate maps has advanced in recent years. However, the mapping accuracy relies heavily on the quality of input layers, the algorithm chosen, and the size and quality of inventory samples for calibration and validation. Results By using airborne lidar data as the “truth” and focusing on the mean canopy height (MCH as a key structural parameter, we test two commonly-used non-parametric techniques of maximum entropy (ME and random forest (RF for developing maps over a study site in Central Gabon. Results of mapping show that both approaches have improved accuracy with more input layers in mapping canopy height at 100 m (1-ha pixels. The bias-corrected spatial models further improve estimates for small and large trees across the tails of height distributions with a trade-off in increasing overall mean squared error that can be readily compensated by increasing the sample size. Conclusions A significant improvement in tropical forest mapping can be achieved by weighting the number of inventory samples against the choice of image layers and the non-parametric algorithms. Without future satellite observations with better sensitivity to forest biomass, the maps based on existing data will remain slightly biased towards the mean of the distribution and under and over estimating the upper and lower tails of the distribution.

Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain.

Science.gov (United States)

Fang, Jinsheng; Bao, Lijun; Li, Xu; van Zijl, Peter C M; Chen, Zhong

2017-08-01

Background field removal is an important MR phase preprocessing step for quantitative susceptibility mapping (QSM). It separates the local field induced by tissue magnetic susceptibility sources from the background field generated by sources outside a region of interest, e.g. brain, such as air-tissue interface. In the vicinity of air-tissue boundary, e.g. skull and paranasal sinuses, where large susceptibility variations exist, present background field removal methods are usually insufficient and these regions often need to be excluded by brain mask erosion at the expense of losing information of local field and thus susceptibility measures in these regions. In this paper, we propose an extension to the variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP) background field removal method using a region adaptive kernel (R-SHARP), in which a scalable spherical Gaussian kernel (SGK) is employed with its kernel radius and weights adjustable according to an energy "functional" reflecting the magnitude of field variation. Such an energy functional is defined in terms of a contour and two fitting functions incorporating regularization terms, from which a curve evolution model in level set formation is derived for energy minimization. We utilize it to detect regions of with a large field gradient caused by strong susceptibility variation. In such regions, the SGK will have a small radius and high weight at the sphere center in a manner adaptive to the voxel energy of the field perturbation. Using the proposed method, the background field generated from external sources can be effectively removed to get a more accurate estimation of the local field and thus of the QSM dipole inversion to map local tissue susceptibility sources. Numerical simulation, phantom and in vivo human brain data demonstrate improved performance of R-SHARP compared to V-SHARP and RESHARP (regularization enabled SHARP) methods, even when the whole paranasal sinus regions

Bias-dependent high saturation solar LBIC scanning of solar cells

Energy Technology Data Exchange (ETDEWEB)

Vorster, F.J.; van Dyk, E.E. [Department of Physics, Nelson Mandela Metropolitan University, P.O. Box 77000, Port Elizabeth 6031 (South Africa)

2007-06-15

A light beam-induced current measurement system that uses concentrated solar radiation as a beam probe to map spatially distributed defects on a solar cell has been developed and tested [F.J. Vorster, E.E. van Dyk, Rev. Sci. Instrum., submitted for review]. The induced current response from a flat plate EFG Si solar cell was mapped as a function of surface position and cell bias by using a solar light beam induced current (S-LBIC) mapping system while at the same time dynamically biasing the whole cell with an external voltage. This paper examines the issues relating to transient capacitive effects as well as the electrical behaviour of typical solar cell defect mechanisms under spot illumination. By examining the bias dependence of the S-LBIC maps, various defect mechanisms of photovoltaic (PV) cells under concentrated solar irradiance may be identified. The techniques employed to interpret the spatially distributed IV curves as well as initial results are discussed. (author)

Characterization of myocardial T1-mapping bias caused by intramyocardial fat in inversion recovery and saturation recovery techniques

DEFF Research Database (Denmark)

Kellman, Peter; Bandettini, W Patricia; Mancini, Christine

2015-01-01

BACKGROUND: Quantitative measurement of T1 in the myocardium may be used to detect both focal and diffuse disease processes such as interstitial fibrosis or edema. A partial volume problem exists when a voxel in the myocardium also contains fat. Partial volume with fat occurs at tissue boundaries...... imaging protocols using balanced steady state free precession are considered. In-vivo imaging with T1-mapping, water/fat separated imaging, and late enhancement imaging was performed on subjects with chronic myocardial infarction. RESULTS: In n = 17 subjects with chronic myocardial infarction, lipomatous...... agreement with simulation of the specific imaging protocols. CONCLUSIONS: Measurement of the myocardial T1 by widely used balanced steady state free precession mapping methods is subject to bias when there is a mixture of water and fat in the myocardium. Intramyocardial fat is frequently present...

Reduction of density-modification bias by β correction

International Nuclear Information System (INIS)

Skubák, Pavol; Pannu, Navraj S.

2011-01-01

A cross-validation-based method for bias reduction in ‘classical’ iterative density modification of experimental X-ray crystallography maps provides significantly more accurate phase-quality estimates and leads to improved automated model building. Density modification often suffers from an overestimation of phase quality, as seen by escalated figures of merit. A new cross-validation-based method to address this estimation bias by applying a bias-correction parameter ‘β’ to maximum-likelihood phase-combination functions is proposed. In tests on over 100 single-wavelength anomalous diffraction data sets, the method is shown to produce much more reliable figures of merit and improved electron-density maps. Furthermore, significantly better results are obtained in automated model building iterated with phased refinement using the more accurate phase probability parameters from density modification

Wind-Farm Forecasting Using the HARMONIE Weather Forecast Model and Bayes Model Averaging for Bias Removal.

Science.gov (United States)

O'Brien, Enda; McKinstry, Alastair; Ralph, Adam

2015-04-01

Building on previous work presented at EGU 2013 (http://www.sciencedirect.com/science/article/pii/S1876610213016068 ), more results are available now from a different wind-farm in complex terrain in southwest Ireland. The basic approach is to interpolate wind-speed forecasts from an operational weather forecast model (i.e., HARMONIE in the case of Ireland) to the precise location of each wind-turbine, and then use Bayes Model Averaging (BMA; with statistical information collected from a prior training-period of e.g., 25 days) to remove systematic biases. Bias-corrected wind-speed forecasts (and associated power-generation forecasts) are then provided twice daily (at 5am and 5pm) out to 30 hours, with each forecast validation fed back to BMA for future learning. 30-hr forecasts from the operational Met Éireann HARMONIE model at 2.5km resolution have been validated against turbine SCADA observations since Jan. 2014. An extra high-resolution (0.5km grid-spacing) HARMONIE configuration has been run since Nov. 2014 as an extra member of the forecast "ensemble". A new version of HARMONIE with extra filters designed to stabilize high-resolution configurations has been run since Jan. 2015. Measures of forecast skill and forecast errors will be provided, and the contributions made by the various physical and computational enhancements to HARMONIE will be quantified.

Some design considerations for perpendicular biased ferrite tuners

International Nuclear Information System (INIS)

Enchevich, I.B.; Poirier, R.L.

1994-10-01

Recently remarkable progress has been achieved in the development of perpendicular biased ferrite tuned rf resonators for fast cycled synchrotrons. Compared with the broadly used parallel biased rf cavities they provide higher resonator quality factor Q. However when designing perpendicular biased cavities, special attention should be paid to the methods to provide eddy current suppression in the resonator walls, the ferrite nonlinearity influence, the generated heat removal, the fast self resonant frequency control. The prospective of a faster additional biasing system are discussed and conclusions are drawn. (author). 8 refs., 6 figs

A scoping review of weight bias by community pharmacists towards people with obesity and mental illness.

Science.gov (United States)

Murphy, Andrea L; Gardner, David M

2016-07-01

Community pharmacists are accessible health care professionals who are increasingly offering weight management programs. People living with serious mental illness have markedly higher rates of obesity and associated illness outcomes than the general population, providing pharmacists who are interested in offering weight management services with an identifiable patient subgroup with increased health needs. Issues with stigma within obesity and mental illness care are prevalent and can lead to inequities and reduced quality of care. We conducted a scoping review to map and characterize the available information from published and grey literature sources regarding community pharmacists and weight bias towards obese people with lived experience of mental illness. A staged approach to the scoping review was used. Six articles and 6 websites were abstracted after we removed duplicates and applied our inclusion and exclusion criteria. The published studies that we found indicated that pharmacists and pharmacy students do demonstrate implicit and explicit weight bias. Very limited research is available regarding weight bias in pharmacists and stigma towards people with obesity, and we found no information on these phenomena relating to people with lived experience of mental illness. Investigations are needed to characterize the extent and nature of anti-fat bias and attitudes by pharmacists and the consequences of these attitudes for patient care.

A simple correction to remove the bias of the gini coefficient due to grouping

NARCIS (Netherlands)

T.G.M. van Ourti (Tom); Ph. Clarke (Philip)

2011-01-01

textabstractAbstract-We propose a first-order bias correction term for the Gini index to reduce the bias due to grouping. It depends on only the number of individuals in each group and is derived from a measurement error framework. We also provide a formula for the remaining second-order bias. Both

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

Science.gov (United States)

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-01-01

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

Science.gov (United States)

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-06-15

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

Directory of Open Access Journals (Sweden)

Haris Akram Bhatti

2016-06-01

Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Stochasticity in the Josephson map

International Nuclear Information System (INIS)

Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.

1996-04-01

The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)

Numerical value biases sound localization.

Science.gov (United States)

Golob, Edward J; Lewald, Jörg; Getzmann, Stephan; Mock, Jeffrey R

2017-12-08

Speech recognition starts with representations of basic acoustic perceptual features and ends by categorizing the sound based on long-term memory for word meaning. However, little is known about whether the reverse pattern of lexical influences on basic perception can occur. We tested for a lexical influence on auditory spatial perception by having subjects make spatial judgments of number stimuli. Four experiments used pointing or left/right 2-alternative forced choice tasks to examine perceptual judgments of sound location as a function of digit magnitude (1-9). The main finding was that for stimuli presented near the median plane there was a linear left-to-right bias for localizing smaller-to-larger numbers. At lateral locations there was a central-eccentric location bias in the pointing task, and either a bias restricted to the smaller numbers (left side) or no significant number bias (right side). Prior number location also biased subsequent number judgments towards the opposite side. Findings support a lexical influence on auditory spatial perception, with a linear mapping near midline and more complex relations at lateral locations. Results may reflect coding of dedicated spatial channels, with two representing lateral positions in each hemispace, and the midline area represented by either their overlap or a separate third channel.

Towards quantitative off-axis electron holographic mapping of the electric field around the tip of a sharp biased metallic needle

DEFF Research Database (Denmark)

Beleggia, Marco; Kasama, Takeshi; Larson, D. J.

2014-01-01

We apply off-axis electron holography and Lorentz microscopy in the transmission electron microscope to map the electric field generated by a sharp biased metallic tip. A combination of experimental data and modelling provides quantitative information about the potential and the field around...... the tip. Close to the tip apex, we measure a maximum field intensity of 82 MV/m, corresponding to a field k factor of 2.5, in excellent agreement with theory. In order to verify the validity of the measurements, we use the inferred charge density distribution in the tip region to generate simulated phase...

Blind signal processing algorithms under DC biased Gaussian noise

Science.gov (United States)

Kim, Namyong; Byun, Hyung-Gi; Lim, Jeong-Ok

2013-05-01

Distortions caused by the DC-biased laser input can be modeled as DC biased Gaussian noise and removing DC bias is important in the demodulation process of the electrical signal in most optical communications. In this paper, a new performance criterion and a related algorithm for unsupervised equalization are proposed for communication systems in the environment of channel distortions and DC biased Gaussian noise. The proposed criterion utilizes the Euclidean distance between the Dirac-delta function located at zero on the error axis and a probability density function of biased constant modulus errors, where constant modulus error is defined by the difference between the system out and a constant modulus calculated from the transmitted symbol points. From the results obtained from the simulation under channel models with fading and DC bias noise abruptly added to background Gaussian noise, the proposed algorithm converges rapidly even after the interruption of DC bias proving that the proposed criterion can be effectively applied to optical communication systems corrupted by channel distortions and DC bias noise.

Determination of Shift/Bias in Digital Aerial Triangulation of UAV Imagery Sequences

Science.gov (United States)

Wierzbicki, Damian

2017-12-01

Currently UAV Photogrammetry is characterized a largely automated and efficient data processing. Depicting from the low altitude more often gains on the meaning in the uses of applications as: cities mapping, corridor mapping, road and pipeline inspections or mapping of large areas e.g. forests. Additionally, high-resolution video image (HD and bigger) is more often use for depicting from the low altitude from one side it lets deliver a lot of details and characteristics of ground surfaces features, and from the other side is presenting new challenges in the data processing. Therefore, determination of elements of external orientation plays a substantial role the detail of Digital Terrain Models and artefact-free ortophoto generation. Parallel a research on the quality of acquired images from UAV and above the quality of products e.g. orthophotos are conducted. Despite so fast development UAV photogrammetry still exists the necessity of accomplishment Automatic Aerial Triangulation (AAT) on the basis of the observations GPS/INS and via ground control points. During low altitude photogrammetric flight, the approximate elements of external orientation registered by UAV are burdened with the influence of some shift/bias errors. In this article, methods of determination shift/bias error are presented. In the process of the digital aerial triangulation two solutions are applied. In the first method shift/bias error was determined together with the drift/bias error, elements of external orientation and coordinates of ground control points. In the second method shift/bias error was determined together with the elements of external orientation, coordinates of ground control points and drift/bias error equals 0. When two methods were compared the difference for shift/bias error is more than ±0.01 m for all terrain coordinates XYZ.

Spatial uncertainty in bias corrected climate change projections and hydrogeological impacts

DEFF Research Database (Denmark)

Seaby, Lauren Paige; Refsgaard, Jens Christian; Sonnenborg, Torben

2015-01-01

Model pairing, this paper analyses the relationship between complexity and robustness of three distribution-based scaling (DBS) bias correction methods applied to daily precipitation at various spatial scales. Hydrological simulations are forced by CM inputs to assess the spatial uncertainty......The question of which climate model bias correction methods and spatial scales for correction are optimal for both projecting future hydrological changes as well as removing initial model bias has so far received little attention. For 11 climate models (CMs), or GCM/RCM – Global/Regional Climate...... signals. The magnitude of spatial bias seen in precipitation inputs does not necessarily correspond to the magnitude of biases seen in hydrological outputs. Variables that integrate basin responses over time and space are more sensitive to mean spatial biases and less so on extremes. Hydrological...

Motion, identity and the bias toward agency

Directory of Open Access Journals (Sweden)

Chris eFields

2014-08-01

Full Text Available The well-documented human bias toward agency as a cause and therefore an explanation of observed events is typically attributed to evolutionary selection for a social brain. Based on a review of developmental and adult behavioral and neurocognitive data, it is argued that the bias toward agency is a result of the default human solution, developed during infancy, to the computational requirements of object re-identification over gaps in observation of more than a few seconds. If this model is correct, overriding the bias toward agency to construct mechanistic explanations of observed events requires structure-mapping inferences, implemented by the pre-motor action planning system, that replace agents with mechanisms as causes of unobserved changes in contextual or featural properties of objects. Experiments that would test this model are discussed.

Autocalibration method for non-stationary CT bias correction.

Science.gov (United States)

Vegas-Sánchez-Ferrero, Gonzalo; Ledesma-Carbayo, Maria J; Washko, George R; Estépar, Raúl San José

2018-02-01

Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases. Copyright © 2017 Elsevier B.V. All rights reserved.

An experimental verification of laser-velocimeter sampling bias and its correction

Science.gov (United States)

Johnson, D. A.; Modarress, D.; Owen, F. K.

1982-01-01

The existence of 'sampling bias' in individual-realization laser velocimeter measurements is experimentally verified and shown to be independent of sample rate. The experiments were performed in a simple two-stream mixing shear flow with the standard for comparison being laser-velocimeter results obtained under continuous-wave conditions. It is also demonstrated that the errors resulting from sampling bias can be removed by a proper interpretation of the sampling statistics. In addition, data obtained in a shock-induced separated flow and in the near-wake of airfoils are presented, both bias-corrected and uncorrected, to illustrate the effects of sampling bias in the extreme.

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

Science.gov (United States)

Ogura, Tomoo; Shiogama, Hideo; Watanabe, Masahiro; Yoshimori, Masakazu; Yokohata, Tokuta; Annan, James D.; Hargreaves, Julia C.; Ushigami, Naoto; Hirota, Kazuya; Someya, Yu; Kamae, Youichi; Tatebe, Hiroaki; Kimoto, Masahide

2017-12-01

This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used output of a perturbed parameter ensemble (PPE) experiment conducted with an atmosphere-ocean general circulation model (AOGCM) without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5) was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitude-longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

Directory of Open Access Journals (Sweden)

T. Ogura

2017-12-01

Full Text Available This study discusses how much of the biases in top-of-atmosphere (TOA radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5 generation. We used output of a perturbed parameter ensemble (PPE experiment conducted with an atmosphere–ocean general circulation model (AOGCM without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5 was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitude–longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.

Infrared Resummation for Biased Tracers in Redshift Space arXiv

CERN Document Server

Ivanov, Mikhail M.

We incorporate the effects of redshift space distortions and non-linear bias in time-sliced perturbation theory (TSPT). This is done via a new method that allows to map cosmological correlation functions from real to redshift space. This mapping preserves a transparent infrared (IR) structure of the theory and provides us with an efficient tool to study non-linear infrared effects altering the pattern of baryon acoustic oscillations (BAO) in redshift space. We give an accurate description of the BAO by means of a systematic resummation of Feynman diagrams guided by well-defined power counting rules. This establishes IR resummation within TSPT as a robust and complete procedure and provides a consistent theoretical model for the BAO feature in the statistics of biased tracers in redshift space.

Robust Likelihoods for Inflationary Gravitational Waves from Maps of Cosmic Microwave Background Polarization

Science.gov (United States)

Switzer, Eric Ryan; Watts, Duncan J.

2016-01-01

The B-mode polarization of the cosmic microwave background provides a unique window into tensor perturbations from inflationary gravitational waves. Survey effects complicate the estimation and description of the power spectrum on the largest angular scales. The pixel-space likelihood yields parameter distributions without the power spectrum as an intermediate step, but it does not have the large suite of tests available to power spectral methods. Searches for primordial B-modes must rigorously reject and rule out contamination. Many forms of contamination vary or are uncorrelated across epochs, frequencies, surveys, or other data treatment subsets. The cross power and the power spectrum of the difference of subset maps provide approaches to reject and isolate excess variance. We develop an analogous joint pixel-space likelihood. Contamination not modeled in the likelihood produces parameter-dependent bias and complicates the interpretation of the difference map. We describe a null test that consistently weights the difference map. Excess variance should either be explicitly modeled in the covariance or be removed through reprocessing the data.

Geometrical Model of Solar Radiation Pressure Based on High-Performing Galileo Clocks - First Geometrical Mapping of the Yarkowsky effect

Science.gov (United States)

Svehla, Drazen; Rothacher, Markus; Hugentobler, Urs; Steigenberger, Peter; Ziebart, Marek

2014-05-01

Solar radiation pressure is the main source of errors in the precise orbit determination of GNSS satellites. All deficiencies in the modeling of Solar radiation pressure map into estimated terrestrial reference frame parameters as well as into derived gravity field coefficients and altimetry results when LEO orbits are determined using GPS. Here we introduce a new approach to geometrically map radial orbit perturbations of GNSS satellites using highly-performing clocks on board the first Galileo satellites. Only a linear model (time bias and time drift) needs to be removed from the estimated clock parameters and the remaining clock residuals map all radial orbit perturbations along the orbit. With the independent SLR measurements, we show that a Galileo clock is stable enough to map radial orbit perturbations continuously along the orbit with a negative sign in comparison to SLR residuals. Agreement between the SLR residuals and the clock residuals is at the 1 cm RMS for an orbit arc of 24 h. Looking at the clock parameters determined along one orbit revolution over a period of one year, we show that the so-called SLR bias in Galileo and GPS orbits can be explained by the translation of the determined orbit in the orbital plane towards the Sun. This orbit translation is due to thermal re-radiation and not accounting for the Sun elevation in the parameterization of the estimated Solar radiation pressure parameters. SLR ranging to GNSS satellites takes place typically at night, e.g. between 6 pm and 6 am local time when the Sun is in opposition to the satellite. Therefore, SLR observes only one part of the GNSS orbit with a negative radial orbit error that is mapped as an artificial bias in SLR observables. The Galileo clocks clearly show orbit translation for all Sun elevations: the radial orbit error is positive when the Sun is in conjuction (orbit noon) and negative when the Sun is in opposition (orbit midnight). The magnitude of this artificial negative SLR bias

Bias against research on gender bias.

Science.gov (United States)

Cislak, Aleksandra; Formanowicz, Magdalena; Saguy, Tamar

2018-01-01

The bias against women in academia is a documented phenomenon that has had detrimental consequences, not only for women, but also for the quality of science. First, gender bias in academia affects female scientists, resulting in their underrepresentation in academic institutions, particularly in higher ranks. The second type of gender bias in science relates to some findings applying only to male participants, which produces biased knowledge. Here, we identify a third potentially powerful source of gender bias in academia: the bias against research on gender bias. In a bibliometric investigation covering a broad range of social sciences, we analyzed published articles on gender bias and race bias and established that articles on gender bias are funded less often and published in journals with a lower Impact Factor than articles on comparable instances of social discrimination. This result suggests the possibility of an underappreciation of the phenomenon of gender bias and related research within the academic community. Addressing this meta-bias is crucial for the further examination of gender inequality, which severely affects many women across the world.

Bias correction for magnetic resonance images via joint entropy regularization.

Science.gov (United States)

Wang, Shanshan; Xia, Yong; Dong, Pei; Luo, Jianhua; Huang, Qiu; Feng, Dagan; Li, Yuanxiang

2014-01-01

Due to the imperfections of the radio frequency (RF) coil or object-dependent electrodynamic interactions, magnetic resonance (MR) images often suffer from a smooth and biologically meaningless bias field, which causes severe troubles for subsequent processing and quantitative analysis. To effectively restore the original signal, this paper simultaneously exploits the spatial and gradient features of the corrupted MR images for bias correction via the joint entropy regularization. With both isotropic and anisotropic total variation (TV) considered, two nonparametric bias correction algorithms have been proposed, namely IsoTVBiasC and AniTVBiasC. These two methods have been applied to simulated images under various noise levels and bias field corruption and also tested on real MR data. The test results show that the proposed two methods can effectively remove the bias field and also present comparable performance compared to the state-of-the-art methods.

Modeling Temporal Bias of Uplift Events in Recommender Systems

KAUST Repository

Altaf, Basmah

2013-05-08

Today, commercial industry spends huge amount of resources in advertisement campaigns, new marketing strategies, and promotional deals to introduce their product to public and attract a large number of customers. These massive investments by a company are worthwhile because marketing tactics greatly influence the consumer behavior. Alternatively, these advertising campaigns have a discernible impact on recommendation systems which tend to promote popular items by ranking them at the top, resulting in biased and unfair decision making and loss of customers’ trust. The biasing impact of popularity of items on recommendations, however, is not fixed, and varies with time. Therefore, it is important to build a bias-aware recommendation system that can rank or predict items based on their true merit at given time frame. This thesis proposes a framework that can model the temporal bias of individual items defined by their characteristic contents, and provides a simple process for bias correction. Bias correction is done either by cleaning the bias from historical training data that is used for building predictive model, or by ignoring the estimated bias from the predictions of a standard predictor. Evaluated on two real world datasets, NetFlix and MovieLens, our framework is shown to be able to estimate and remove the bias as a result of adopted marketing techniques from the predicted popularity of items at a given time.

Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset

Science.gov (United States)

Lange, Stefan

2018-05-01

Many meteorological forcing datasets include bias-corrected surface downwelling longwave and shortwave radiation (rlds and rsds). Methods used for such bias corrections range from multi-year monthly mean value scaling to quantile mapping at the daily timescale. An additional downscaling is necessary if the data to be corrected have a higher spatial resolution than the observational data used to determine the biases. This was the case when EartH2Observe (E2OBS; Calton et al., 2016) rlds and rsds were bias-corrected using more coarsely resolved Surface Radiation Budget (SRB; Stackhouse Jr. et al., 2011) data for the production of the meteorological forcing dataset EWEMBI (Lange, 2016). This article systematically compares various parametric quantile mapping methods designed specifically for this purpose, including those used for the production of EWEMBI rlds and rsds. The methods vary in the timescale at which they operate, in their way of accounting for physical upper radiation limits, and in their approach to bridging the spatial resolution gap between E2OBS and SRB. It is shown how temporal and spatial variability deflation related to bilinear interpolation and other deterministic downscaling approaches can be overcome by downscaling the target statistics of quantile mapping from the SRB to the E2OBS grid such that the sub-SRB-grid-scale spatial variability present in the original E2OBS data is retained. Cross validations at the daily and monthly timescales reveal that it is worthwhile to take empirical estimates of physical upper limits into account when adjusting either radiation component and that, overall, bias correction at the daily timescale is more effective than bias correction at the monthly timescale if sampling errors are taken into account.

Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset

Directory of Open Access Journals (Sweden)

S. Lange

2018-05-01

Full Text Available Many meteorological forcing datasets include bias-corrected surface downwelling longwave and shortwave radiation (rlds and rsds. Methods used for such bias corrections range from multi-year monthly mean value scaling to quantile mapping at the daily timescale. An additional downscaling is necessary if the data to be corrected have a higher spatial resolution than the observational data used to determine the biases. This was the case when EartH2Observe (E2OBS; Calton et al., 2016 rlds and rsds were bias-corrected using more coarsely resolved Surface Radiation Budget (SRB; Stackhouse Jr. et al., 2011 data for the production of the meteorological forcing dataset EWEMBI (Lange, 2016. This article systematically compares various parametric quantile mapping methods designed specifically for this purpose, including those used for the production of EWEMBI rlds and rsds. The methods vary in the timescale at which they operate, in their way of accounting for physical upper radiation limits, and in their approach to bridging the spatial resolution gap between E2OBS and SRB. It is shown how temporal and spatial variability deflation related to bilinear interpolation and other deterministic downscaling approaches can be overcome by downscaling the target statistics of quantile mapping from the SRB to the E2OBS grid such that the sub-SRB-grid-scale spatial variability present in the original E2OBS data is retained. Cross validations at the daily and monthly timescales reveal that it is worthwhile to take empirical estimates of physical upper limits into account when adjusting either radiation component and that, overall, bias correction at the daily timescale is more effective than bias correction at the monthly timescale if sampling errors are taken into account.

THE SLOAN DIGITAL SKY SURVEY REVERBERATION MAPPING PROJECT: BIASES IN z  > 1.46 REDSHIFTS DUE TO QUASAR DIVERSITY

Energy Technology Data Exchange (ETDEWEB)

Denney, K. D.; Peterson, B. M. [Department of Astronomy, The Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States); Horne, Keith [SUPA Physics and Astronomy, University of St. Andrews, St. Andrews KY16 9SS (United Kingdom); Brandt, W. N.; Grier, C. J.; Trump, J. R. [Department of Astronomy and Astrophysics, 525 Davey Lab, The Pennsylvania State University, University Park, PA 16802 (United States); Ho, Luis C. [Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871 (China); Ge, J., E-mail: denney@astronomy.ohio-state.edu [Astronomy Department University of Florida 211 Bryant Space Science Center P.O. Box 112055 Gainesville, FL 32611-2055 (United States)

2016-12-10

We use the coadded spectra of 32 epochs of Sloan Digital Sky Survey (SDSS) Reverberation Mapping Project observations of 482 quasars with z  > 1.46 to highlight systematic biases in the SDSS- and Baryon Oscillation Spectroscopic Survey (BOSS)-pipeline redshifts due to the natural diversity of quasar properties. We investigate the characteristics of this bias by comparing the BOSS-pipeline redshifts to an estimate from the centroid of He ii λ 1640. He ii has a low equivalent width but is often well-defined in high-S/N spectra, does not suffer from self-absorption, and has a narrow component which, when present (the case for about half of our sources), produces a redshift estimate that, on average, is consistent with that determined from [O ii] to within the He ii and [O ii] centroid measurement uncertainties. The large redshift differences of ∼1000 km s{sup −1}, on average, between the BOSS-pipeline and He ii-centroid redshifts, suggest there are significant biases in a portion of BOSS quasar redshift measurements. Adopting the He ii-based redshifts shows that C iv does not exhibit a ubiquitous blueshift for all quasars, given the precision probed by our measurements. Instead, we find a distribution of C iv-centroid blueshifts across our sample, with a dynamic range that (i) is wider than that previously reported for this line, and (ii) spans C iv centroids from those consistent with the systemic redshift to those with significant blueshifts of thousands of kilometers per second. These results have significant implications for measurement and use of high-redshift quasar properties and redshifts, and studies based thereon.

THE SLOAN DIGITAL SKY SURVEY REVERBERATION MAPPING PROJECT: BIASES IN z  > 1.46 REDSHIFTS DUE TO QUASAR DIVERSITY

International Nuclear Information System (INIS)

Denney, K. D.; Peterson, B. M.; Horne, Keith; Brandt, W. N.; Grier, C. J.; Trump, J. R.; Ho, Luis C.; Ge, J.

2016-01-01

We use the coadded spectra of 32 epochs of Sloan Digital Sky Survey (SDSS) Reverberation Mapping Project observations of 482 quasars with z  > 1.46 to highlight systematic biases in the SDSS- and Baryon Oscillation Spectroscopic Survey (BOSS)-pipeline redshifts due to the natural diversity of quasar properties. We investigate the characteristics of this bias by comparing the BOSS-pipeline redshifts to an estimate from the centroid of He ii λ 1640. He ii has a low equivalent width but is often well-defined in high-S/N spectra, does not suffer from self-absorption, and has a narrow component which, when present (the case for about half of our sources), produces a redshift estimate that, on average, is consistent with that determined from [O ii] to within the He ii and [O ii] centroid measurement uncertainties. The large redshift differences of ∼1000 km s −1 , on average, between the BOSS-pipeline and He ii-centroid redshifts, suggest there are significant biases in a portion of BOSS quasar redshift measurements. Adopting the He ii-based redshifts shows that C iv does not exhibit a ubiquitous blueshift for all quasars, given the precision probed by our measurements. Instead, we find a distribution of C iv-centroid blueshifts across our sample, with a dynamic range that (i) is wider than that previously reported for this line, and (ii) spans C iv centroids from those consistent with the systemic redshift to those with significant blueshifts of thousands of kilometers per second. These results have significant implications for measurement and use of high-redshift quasar properties and redshifts, and studies based thereon.

Assessing implicit gender bias in Medical Student Performance Evaluations.

Science.gov (United States)

Axelson, Rick D; Solow, Catherine M; Ferguson, Kristi J; Cohen, Michael B

2010-09-01

For medical schools, the increasing presence of women makes it especially important that potential sources of gender bias be identified and removed from student evaluation methods. Our study looked for patterns of gender bias in adjective data used to inform our Medical Student Performance Evaluations (MSPEs). Multigroup Confirmatory Factor Analysis (CFA) was used to model the latent structure of the adjectives attributed to students (n = 657) and to test for systematic scoring errors by gender. Gender bias was evident in two areas: (a) women were more likely than comparable men to be described as ''compassionate,'' ''sensitive,'' and ''enthusiastic'' and (b) men were more likely than comparable women to be seen as ''quick learners.'' The gender gap in ''quick learner'' attribution grows with increasing student proficiency; men's rate of increase is over twice that of women's. Technical and nontechnical approaches for ameliorating the impact of gender bias on student recommendations are suggested.

Mapping and Assessment of PM10 and O3 Removal by Woody Vegetation at Urban and Regional Level

Directory of Open Access Journals (Sweden)

Lina Fusaro

2017-08-01

Full Text Available This study is the follow up of the URBAN-MAES pilot implemented in the framework of the EnRoute project. The study aims at mapping and assessing the process of particulate matter (PM10 and tropospheric ozone (O3 removal by various forest and shrub ecosystems. Different policy levels and environmental contexts were considered, namely the Metropolitan city of Rome and, at a wider level, the Latium region. The approach involves characterization of the main land cover and ecosystems using Sentinel-2 images, enabling a detailed assessment of Ecosystem Service (ES, and monetary valuation based on externality values. The results showed spatial variations in the pattern of PM10 and O3 removal inside the Municipality and in the more rural Latium hinterland, reflecting the spatial dynamics of the two pollutants. Evergreen species displayed higher PM10 removal efficiency, whereas deciduous species showed higher O3 absorption in both rural and urban areas. The overall pollution removal accounted for 5123 and 19,074 Mg of PM10 and O3, respectively, with a relative monetary benefit of 161 and 149 Million Euro for PM10 and O3, respectively. Our results provide spatially explicit evidence that may assist policymakers in land-oriented decisions towards improving Green Infrastructure and maximizing ES provision at different governance levels.

Correcting bias in the rational polynomial coefficients of satellite imagery using thin-plate smoothing splines

Science.gov (United States)

Shen, Xiang; Liu, Bin; Li, Qing-Quan

2017-03-01

The Rational Function Model (RFM) has proven to be a viable alternative to the rigorous sensor models used for geo-processing of high-resolution satellite imagery. Because of various errors in the satellite ephemeris and instrument calibration, the Rational Polynomial Coefficients (RPCs) supplied by image vendors are often not sufficiently accurate, and there is therefore a clear need to correct the systematic biases in order to meet the requirements of high-precision topographic mapping. In this paper, we propose a new RPC bias-correction method using the thin-plate spline modeling technique. Benefiting from its excellent performance and high flexibility in data fitting, the thin-plate spline model has the potential to remove complex distortions in vendor-provided RPCs, such as the errors caused by short-period orbital perturbations. The performance of the new method was evaluated by using Ziyuan-3 satellite images and was compared against the recently developed least-squares collocation approach, as well as the classical affine-transformation and quadratic-polynomial based methods. The results show that the accuracies of the thin-plate spline and the least-squares collocation approaches were better than the other two methods, which indicates that strong non-rigid deformations exist in the test data because they cannot be adequately modeled by simple polynomial-based methods. The performance of the thin-plate spline method was close to that of the least-squares collocation approach when only a few Ground Control Points (GCPs) were used, and it improved more rapidly with an increase in the number of redundant observations. In the test scenario using 21 GCPs (some of them located at the four corners of the scene), the correction residuals of the thin-plate spline method were about 36%, 37%, and 19% smaller than those of the affine transformation method, the quadratic polynomial method, and the least-squares collocation algorithm, respectively, which demonstrates

Ammonium nitrogen removal from coking wastewater by chemical precipitation recycle technology.

Science.gov (United States)

Zhang, Tao; Ding, Lili; Ren, Hongqiang; Xiong, Xiang

2009-12-01

Ammonium nitrogen removal from wastewater has been of considerable concern for several decades. In the present research, we examined chemical precipitation recycle technology (CPRT) for ammonium nitrogen removal from coking wastewater. The pyrolysate resulting from magnesium ammonium phosphate (MAP) pyrogenation in sodium hydroxide (NaOH) solution was recycled for ammonium nitrogen removal from coking wastewater. The objective of this study was to investigate the conditions for MAP pyrogenation and to characterize of MAP pyrolysate for its feasibility in recycling. Furthermore, MAP pyrolysate was characterized by scanning electron microscope (FESEM), transmission electron microscope (TEM), Fourier transform infrared spectroscopy (FTIR) as well as X-ray diffraction (XRD). The MAP pyrolysate could be produced at the optimal condition of a hydroxyl (OH(-)) to ammonium molar ratio of 2:1, a heating temperature of 110 degrees C, and a heating time of 3h. Surface characterization analysis indicated that the main component of the pyrolysate was amorphous magnesium sodium phosphate (MgNaPO(4)). The pyrolysate could be recycled as a magnesium and phosphate source at an optimum pH of 9.5. When the recycle times were increased, the ammonium nitrogen removal ratio gradually decreased if the pyrolysate was used without supplementation. When the recycle times were increased, the ammonium nitrogen removal efficiency was not decreased if the added pyrolysate was supplemented with MgCl(2).6H(2)O plus Na(2)HPO(4).12H(2)O during treatment. A high ammonium nitrogen removal ratio was obtained by using pre-formed MAP as seeding material.

Editorial Bias in Crowd-Sourced Political Information.

Directory of Open Access Journals (Sweden)

Joshua L Kalla

Full Text Available The Internet has dramatically expanded citizens' access to and ability to engage with political information. On many websites, any user can contribute and edit "crowd-sourced" information about important political figures. One of the most prominent examples of crowd-sourced information on the Internet is Wikipedia, a free and open encyclopedia created and edited entirely by users, and one of the world's most accessed websites. While previous studies of crowd-sourced information platforms have found them to be accurate, few have considered biases in what kinds of information are included. We report the results of four randomized field experiments that sought to explore what biases exist in the political articles of this collaborative website. By randomly assigning factually true but either positive or negative and cited or uncited information to the Wikipedia pages of U.S. senators, we uncover substantial evidence of an editorial bias toward positivity on Wikipedia: Negative facts are 36% more likely to be removed by Wikipedia editors than positive facts within 12 hours and 29% more likely within 3 days. Although citations substantially increase an edit's survival time, the editorial bias toward positivity is not eliminated by inclusion of a citation. We replicate this study on the Wikipedia pages of deceased as well as recently retired but living senators and find no evidence of an editorial bias in either. Our results demonstrate that crowd-sourced information is subject to an editorial bias that favors the politically active.

Editorial Bias in Crowd-Sourced Political Information.

Science.gov (United States)

Kalla, Joshua L; Aronow, Peter M

2015-01-01

The Internet has dramatically expanded citizens' access to and ability to engage with political information. On many websites, any user can contribute and edit "crowd-sourced" information about important political figures. One of the most prominent examples of crowd-sourced information on the Internet is Wikipedia, a free and open encyclopedia created and edited entirely by users, and one of the world's most accessed websites. While previous studies of crowd-sourced information platforms have found them to be accurate, few have considered biases in what kinds of information are included. We report the results of four randomized field experiments that sought to explore what biases exist in the political articles of this collaborative website. By randomly assigning factually true but either positive or negative and cited or uncited information to the Wikipedia pages of U.S. senators, we uncover substantial evidence of an editorial bias toward positivity on Wikipedia: Negative facts are 36% more likely to be removed by Wikipedia editors than positive facts within 12 hours and 29% more likely within 3 days. Although citations substantially increase an edit's survival time, the editorial bias toward positivity is not eliminated by inclusion of a citation. We replicate this study on the Wikipedia pages of deceased as well as recently retired but living senators and find no evidence of an editorial bias in either. Our results demonstrate that crowd-sourced information is subject to an editorial bias that favors the politically active.

A basis for bias in geographical judgments.

Science.gov (United States)

Friedman, Alinda; Brown, Norman R; McGaffey, Aaron P

2002-03-01

To determine why North Americans tend to locate European cities south of North American cities at similar latitudes (Tversky, 1981), we had observers provide bearing estimates between cities in the U.S. and Europe. Earlier research using latitude estimates of these cities has indicated that each continent has several subjective regions (Friedman & Brown, 2000a). Participants judged cities from two subjectively northern regions (Milwaukee-Munich), two subjectively southern regions (Memphis-Lisbon), and the two "crossed" regions (Albuquerque-Geneva; Minneapolis-Rome). Estimates were biased only when cities from the subjectively northern regions of North America were paired with cities from the subjectively southern region of Europe. In contrast to the view that biases are derived from distorted or aligned map-like representations, the data provide evidence that the subjective representation of global geography is principally categorical. Biases in numerical location estimates of individual cities and in bearing estimates between city pairs are derived from plausible reasoning processes operating on the same categorical representations.

Long-term biases in geomagnetic K and aa indices

Science.gov (United States)

Love, J.J.

2011-01-01

Analysis is made of the geomagnetic-activity aa index and its source K-index data from groups of ground-based observatories in Britain, and Australia, 1868.0-2009.0, solar cycles 11-23. The K data show persistent biases, especially for high (low) K-activity levels at British (Australian) observatories. From examination of multiple subsets of the K data we infer that the biases are not predominantly the result of changes in observatory location, localized induced magnetotelluric currents, changes in magnetometer technology, or the modernization of K-value estimation methods. Instead, the biases appear to be artifacts of the latitude-dependent scaling used to assign K values to particular local levels of geomagnetic activity. The biases are not effectively removed by weighting factors used to estimate aa. We show that long-term averages of the aa index, such as annual averages, are dominated by medium-level geomagnetic activity levels having K values of 3 and 4. ?? 2011 Author(s).

Long-term biases in geomagnetic K and aa indices

Directory of Open Access Journals (Sweden)

J. J. Love

2011-08-01

Full Text Available Analysis is made of the geomagnetic-activity aa index and its source K-index data from groups of ground-based observatories in Britain, and Australia, 1868.0–2009.0, solar cycles 11–23. The K data show persistent biases, especially for high (low K-activity levels at British (Australian observatories. From examination of multiple subsets of the K data we infer that the biases are not predominantly the result of changes in observatory location, localized induced magnetotelluric currents, changes in magnetometer technology, or the modernization of K-value estimation methods. Instead, the biases appear to be artifacts of the latitude-dependent scaling used to assign K values to particular local levels of geomagnetic activity. The biases are not effectively removed by weighting factors used to estimate aa. We show that long-term averages of the aa index, such as annual averages, are dominated by medium-level geomagnetic activity levels having K values of 3 and 4.

A Realization of Bias Correction Method in the GMAO Coupled System

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Chang, Yehui; Koster, Randal; Wang, Hailan; Schubert, Siegfried; Suarez, Max

2018-01-01

Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of the climate system. The cold or warm sea surface temperature (SST) bias in the tropics is still a problem common to most coupled ocean atmosphere general circulation models (CGCMs). The precipitation biases in CGCMs are also accompanied by SST and surface wind biases. The deficiencies and biases over the equatorial oceans through their influence on the Walker circulation likely contribute the precipitation biases over land surfaces. In this study, we introduce an approach in the CGCM modeling to correct model biases. This approach utilizes the history of the model's short-term forecasting errors and their seasonal dependence to modify model's tendency term and to minimize its climate drift. The study shows that such an approach removes most of model climate biases. A number of other aspects of the model simulation (e.g. extratropical transient activities) are also improved considerably due to the imposed pre-processed initial 3-hour model drift corrections. Because many regional biases in the GEOS-5 CGCM are common amongst other current models, our approaches and findings are applicable to these other models as well.

Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

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Rosenberger, Amanda E.; Dunham, Jason B.

2005-01-01

Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

ALT-II toroidal belt limiter biasing experiments on TEXTOR

International Nuclear Information System (INIS)

Doerner, R.; Boedo, J.A.; Gray, D.S.

1991-01-01

Edge electric fields have been related to H-mode-like behaviour. The experiments reported here are an attempt to control the SOL profiles by electrostatic biasing of the full toroidal-belt limiter ALT-II. The specific goals are: influencing the edge particle flows, particle removal, power deposition and the global confinement. The ALT-II pump limiter is a full toroidal belt located at 45 o below the outer midplane and consisting of eight graphite covered blades which can be independently biased. Particle scoops located behind the limiter neutralize and direct the incoming plasma into the pumping ducts. (author) 5 refs., 3 figs

Intrinsic frequency biases and profiles across human cortex.

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Mellem, Monika S; Wohltjen, Sophie; Gotts, Stephen J; Ghuman, Avniel Singh; Martin, Alex

2017-11-01

Recent findings in monkeys suggest that intrinsic periodic spiking activity in selective cortical areas occurs at timescales that follow a sensory or lower order-to-higher order processing hierarchy (Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ. Nat Neurosci 17: 1661-1663, 2014). It has not yet been fully explored if a similar timescale hierarchy is present in humans. Additionally, these measures in the monkey studies have not addressed findings that rhythmic activity within a brain area can occur at multiple frequencies. In this study we investigate in humans if regions may be biased toward particular frequencies of intrinsic activity and if a full cortical mapping still reveals an organization that follows this hierarchy. We examined the spectral power in multiple frequency bands (0.5-150 Hz) from task-independent data using magnetoencephalography (MEG). We compared standardized power across bands to find regional frequency biases. Our results demonstrate a mix of lower and higher frequency biases across sensory and higher order regions. Thus they suggest a more complex cortical organization that does not simply follow this hierarchy. Additionally, some regions do not display a bias for a single band, and a data-driven clustering analysis reveals a regional organization with high standardized power in multiple bands. Specifically, theta and beta are both high in dorsal frontal cortex, whereas delta and gamma are high in ventral frontal cortex and temporal cortex. Occipital and parietal regions are biased more narrowly toward alpha power, and ventral temporal lobe displays specific biases toward gamma. Thus intrinsic rhythmic neural activity displays a regional organization but one that is not necessarily hierarchical. NEW & NOTEWORTHY The organization of rhythmic neural activity is not well understood. Whereas it has been postulated that rhythms are organized in a hierarchical manner across

Calibration and assessment of channel-specific biases in microarray data with extended dynamical range.

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Bengtsson, Henrik; Jönsson, Göran; Vallon-Christersson, Johan

2004-11-12

Non-linearities in observed log-ratios of gene expressions, also known as intensity dependent log-ratios, can often be accounted for by global biases in the two channels being compared. Any step in a microarray process may introduce such offsets and in this article we study the biases introduced by the microarray scanner and the image analysis software. By scanning the same spotted oligonucleotide microarray at different photomultiplier tube (PMT) gains, we have identified a channel-specific bias present in two-channel microarray data. For the scanners analyzed it was in the range of 15-25 (out of 65,535). The observed bias was very stable between subsequent scans of the same array although the PMT gain was greatly adjusted. This indicates that the bias does not originate from a step preceding the scanner detector parts. The bias varies slightly between arrays. When comparing estimates based on data from the same array, but from different scanners, we have found that different scanners introduce different amounts of bias. So do various image analysis methods. We propose a scanning protocol and a constrained affine model that allows us to identify and estimate the bias in each channel. Backward transformation removes the bias and brings the channels to the same scale. The result is that systematic effects such as intensity dependent log-ratios are removed, but also that signal densities become much more similar. The average scan, which has a larger dynamical range and greater signal-to-noise ratio than individual scans, can then be obtained. The study shows that microarray scanners may introduce a significant bias in each channel. Such biases have to be calibrated for, otherwise systematic effects such as intensity dependent log-ratios will be observed. The proposed scanning protocol and calibration method is simple to use and is useful for evaluating scanner biases or for obtaining calibrated measurements with extended dynamical range and better precision. The

When POS datasets don’t add up: Combatting sample bias

DEFF Research Database (Denmark)

Hovy, Dirk; Plank, Barbara; Søgaard, Anders

2014-01-01

Several works in Natural Language Processing have recently looked into part-of-speech (POS) annotation of Twitter data and typically used their own data sets. Since conventions on Twitter change rapidly, models often show sample bias. Training on a combination of the existing data sets should help...... overcome this bias and produce more robust models than any trained on the individual corpora. Unfortunately, combining the existing corpora proves difficult: many of the corpora use proprietary tag sets that have little or no overlap. Even when mapped to a common tag set, the different corpora...

QIN DAWG Validation of Gradient Nonlinearity Bias Correction Workflow for Quantitative Diffusion-Weighted Imaging in Multicenter Trials.

Science.gov (United States)

Malyarenko, Dariya I; Wilmes, Lisa J; Arlinghaus, Lori R; Jacobs, Michael A; Huang, Wei; Helmer, Karl G; Taouli, Bachir; Yankeelov, Thomas E; Newitt, David; Chenevert, Thomas L

2016-12-01

Previous research has shown that system-dependent gradient nonlinearity (GNL) introduces a significant spatial bias (nonuniformity) in apparent diffusion coefficient (ADC) maps. Here, the feasibility of centralized retrospective system-specific correction of GNL bias for quantitative diffusion-weighted imaging (DWI) in multisite clinical trials is demonstrated across diverse scanners independent of the scanned object. Using corrector maps generated from system characterization by ice-water phantom measurement completed in the previous project phase, GNL bias correction was performed for test ADC measurements from an independent DWI phantom (room temperature agar) at two offset locations in the bore. The precomputed three-dimensional GNL correctors were retrospectively applied to test DWI scans by the central analysis site. The correction was blinded to reference DWI of the agar phantom at magnet isocenter where the GNL bias is negligible. The performance was evaluated from changes in ADC region of interest histogram statistics before and after correction with respect to the unbiased reference ADC values provided by sites. Both absolute error and nonuniformity of the ADC map induced by GNL (median, 12%; range, -35% to +10%) were substantially reduced by correction (7-fold in median and 3-fold in range). The residual ADC nonuniformity errors were attributed to measurement noise and other non-GNL sources. Correction of systematic GNL bias resulted in a 2-fold decrease in technical variability across scanners (down to site temperature range). The described validation of GNL bias correction marks progress toward implementation of this technology in multicenter trials that utilize quantitative DWI.

Can a Repeated Opt-Out Reminder remove hypothetical bias in discrete choice experiments?

DEFF Research Database (Denmark)

Alemu, Mohammed Hussen; Olsen, Søren Bøye

hypothetical bias in stated DCE. The data originates from a field experiment concerning consumer preferences for a novel food product made from cricket flour. Utilizing a between-subject design with three treatments, we find significantly higher marginal willingness to pay values in hypothetical than...

Including non-public data and studies in systematic reviews and systematic maps.

Science.gov (United States)

Haddaway, Neal R; Collins, Alexandra M; Coughlin, Deborah; Kohl, Christian

2017-02-01

Systematic reviews and maps should be based on the best available evidence, and reviewers should make all reasonable efforts to source and include potentially relevant studies. However, reviewers may not be able to consider all existing evidence, since some data and studies may not be publicly available. Including non-public studies in reviews provides a valuable opportunity to increase systematic review/map comprehensiveness, potentially mitigating negative impacts of publication bias. Studies may be non-public for many reasons: some may still be in the process of being published (publication can take a long time); some may not be published due to author/publisher restrictions; publication bias may make it difficult to publish non-significant or negative results. Here, we consider what forms these non-public studies may take and the implications of including them in systematic reviews and maps. Reviewers should carefully consider the advantages and disadvantages of including non-public studies, weighing risks of bias against benefits of increased comprehensiveness. As with all systematic reviews and maps, reviewers must be transparent about methods used to obtain data and avoid risks of bias in their synthesis. We make tentative suggestions for reviewers in situations where non-public data may be present in an evidence base. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stochastic perturbations in open chaotic systems: random versus noisy maps.

Science.gov (United States)

Bódai, Tamás; Altmann, Eduardo G; Endler, Antonio

2013-04-01

We investigate the effects of random perturbations on fully chaotic open systems. Perturbations can be applied to each trajectory independently (white noise) or simultaneously to all trajectories (random map). We compare these two scenarios by generalizing the theory of open chaotic systems and introducing a time-dependent conditionally-map-invariant measure. For the same perturbation strength we show that the escape rate of the random map is always larger than that of the noisy map. In random maps we show that the escape rate κ and dimensions D of the relevant fractal sets often depend nonmonotonically on the intensity of the random perturbation. We discuss the accuracy (bias) and precision (variance) of finite-size estimators of κ and D, and show that the improvement of the precision of the estimations with the number of trajectories N is extremely slow ([proportionality]1/lnN). We also argue that the finite-size D estimators are typically biased. General theoretical results are combined with analytical calculations and numerical simulations in area-preserving baker maps.

The Extended HANDS Characterization and Analysis of Metric Biases

Science.gov (United States)

Kelecy, T.; Knox, R.; Cognion, R.

The Extended High Accuracy Network Determination System (Extended HANDS) consists of a network of low cost, high accuracy optical telescopes designed to support space surveillance and development of space object characterization technologies. Comprising off-the-shelf components, the telescopes are designed to provide sub arc-second astrometric accuracy. The design and analysis team are in the process of characterizing the system through development of an error allocation tree whose assessment is supported by simulation, data analysis, and calibration tests. The metric calibration process has revealed 1-2 arc-second biases in the right ascension and declination measurements of reference satellite position, and these have been observed to have fairly distinct characteristics that appear to have some dependence on orbit geometry and tracking rates. The work presented here outlines error models developed to aid in development of the system error budget, and examines characteristic errors (biases, time dependence, etc.) that might be present in each of the relevant system elements used in the data collection and processing, including the metric calibration processing. The relevant reference frames are identified, and include the sensor (CCD camera) reference frame, Earth-fixed topocentric frame, topocentric inertial reference frame, and the geocentric inertial reference frame. The errors modeled in each of these reference frames, when mapped into the topocentric inertial measurement frame, reveal how errors might manifest themselves through the calibration process. The error analysis results that are presented use satellite-sensor geometries taken from periods where actual measurements were collected, and reveal how modeled errors manifest themselves over those specific time periods. These results are compared to the real calibration metric data (right ascension and declination residuals), and sources of the bias are hypothesized. In turn, the actual right ascension and

Ensemble stacking mitigates biases in inference of synaptic connectivity

Directory of Open Access Journals (Sweden)

Brendan Chambers

2018-03-01

Full Text Available A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches. Mapping the routing of spikes through local circuitry is crucial for understanding neocortical computation. Under appropriate experimental conditions, these maps can be used to infer likely patterns of synaptic recruitment, linking activity to underlying anatomical connections. Such inferences help to reveal the synaptic implementation of population dynamics and computation. We compare a number of standard functional measures to infer underlying connectivity. We find that regularization impacts measures

On biases in precise point positioning with multi-constellation and multi-frequency GNSS data

International Nuclear Information System (INIS)

El-Mowafy, A; Deo, M; Rizos, C

2016-01-01

Various types of biases in Global Navigation Satellite System (GNSS) data preclude integer ambiguity fixing and degrade solution accuracy when not being corrected during precise point positioning (PPP). In this contribution, these biases are first reviewed, including satellite and receiver hardware biases, differential code biases, differential phase biases, initial fractional phase biases, inter-system receiver time biases, and system time scale offset. PPP models that take account of these biases are presented for two cases using ionosphere-free observations. The first case is when using primary signals that are used to generate precise orbits and clock corrections. The second case applies when using additional signals to the primary ones. In both cases, measurements from single and multiple constellations are addressed. It is suggested that the satellite-related code biases be handled as calibrated quantities that are obtained from multi-GNSS experiment products and the fractional phase cycle biases obtained from a network to allow for integer ambiguity fixing. Some receiver-related biases are removed using between-satellite single differencing, whereas other receiver biases such as inter-system biases are lumped with differential code and phase biases and need to be estimated. The testing results show that the treatment of biases significantly improves solution convergence in the float ambiguity PPP mode, and leads to ambiguity-fixed PPP within a few minutes with a small improvement in solution precision. (paper)

Evaluation of pre-treatment technologies for phosphorous removal from drinking water to mitigate membrane biofouling

Science.gov (United States)

Frolova, M.; Tihomirova, K.; Mežule, L.; Rubulis, J.; Gruškeviča, K.; Juhna, T.

2017-10-01

Membranes are widely used for the treatment of various solutions. However, membrane fouling remains the limiting factor for their usage, setting biofouling as the most severe type of it. Therefore, the production of biologically stable water prior to membranes is important. Since lack of phosphorus may hinder the growth of microorganisms, the aim of this research is to evaluate the effect of microbially available phosphorus (MAP) removal via affordable water pre-treatment methods (adsorption, biofiltration, electrocoagulation) on bacterial growth. Four cylindrical reactors were installed at an artificially recharged groundwater station. Further temperature influence and carbon limitation were tested for biofiltration technology. The amount of MAP and total cell count was measured by flow cytometry. The results showed that at lower temperatures electrocoagulation performed the best, resulting in complete MAP removal (detection limit 6.27x10-3μg P l-1). Sorbent demonstrated MAP removal of 70-90%. Biomass did not have any noteworthy results at +8°C, however, at +19°C MAP removal of around 80% was achieved. Main conclusions obtained within this study are: (i) tested technologies effectively eliminate MAP levels; (ii) temperature has a significant effect on MAP removal in a bioreactor, (iii) multi-barrier approach might be necessary for better P limitation that might prolong operating time of a membrane.

Moisture Forecast Bias Correction in GEOS DAS

Science.gov (United States)

Dee, D.

1999-01-01

Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.

An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment

Science.gov (United States)

Smitha, P. S.; Narasimhan, B.; Sudheer, K. P.; Annamalai, H.

2018-01-01

Regional climate models (RCMs) are used to downscale the coarse resolution General Circulation Model (GCM) outputs to a finer resolution for hydrological impact studies. However, RCM outputs often deviate from the observed climatological data, and therefore need bias correction before they are used for hydrological simulations. While there are a number of methods for bias correction, most of them use monthly statistics to derive correction factors, which may cause errors in the rainfall magnitude when applied on a daily scale. This study proposes a sliding window based daily correction factor derivations that help build reliable daily rainfall data from climate models. The procedure is applied to five existing bias correction methods, and is tested on six watersheds in different climatic zones of India for assessing the effectiveness of the corrected rainfall and the consequent hydrological simulations. The bias correction was performed on rainfall data downscaled using Conformal Cubic Atmospheric Model (CCAM) to 0.5° × 0.5° from two different CMIP5 models (CNRM-CM5.0, GFDL-CM3.0). The India Meteorological Department (IMD) gridded (0.25° × 0.25°) observed rainfall data was considered to test the effectiveness of the proposed bias correction method. The quantile-quantile (Q-Q) plots and Nash Sutcliffe efficiency (NSE) were employed for evaluation of different methods of bias correction. The analysis suggested that the proposed method effectively corrects the daily bias in rainfall as compared to using monthly factors. The methods such as local intensity scaling, modified power transformation and distribution mapping, which adjusted the wet day frequencies, performed superior compared to the other methods, which did not consider adjustment of wet day frequencies. The distribution mapping method with daily correction factors was able to replicate the daily rainfall pattern of observed data with NSE value above 0.81 over most parts of India. Hydrological

The persistence of the attentional bias to regularities in a changing environment.

Science.gov (United States)

Yu, Ru Qi; Zhao, Jiaying

2015-10-01

The environment often is stable, but some aspects may change over time. The challenge for the visual system is to discover and flexibly adapt to the changes. We examined how attention is shifted in the presence of changes in the underlying structure of the environment. In six experiments, observers viewed four simultaneous streams of objects while performing a visual search task. In the first half of each experiment, the stream in the structured location contained regularities, the shapes in the random location were randomized, and gray squares appeared in two neutral locations. In the second half, the stream in the structured or the random location may change. In the first half of all experiments, visual search was facilitated in the structured location, suggesting that attention was consistently biased toward regularities. In the second half, this bias persisted in the structured location when no change occurred (Experiment 1), when the regularities were removed (Experiment 2), or when new regularities embedded in the original or novel stimuli emerged in the previously random location (Experiments 3 and 6). However, visual search was numerically but no longer reliably faster in the structured location when the initial regularities were removed and new regularities were introduced in the previously random location (Experiment 4), or when novel random stimuli appeared in the random location (Experiment 5). This suggests that the attentional bias was weakened. Overall, the results demonstrate that the attentional bias to regularities was persistent but also sensitive to changes in the environment.

Spatial Bias in Field-Estimated Unsaturated Hydraulic Properties

Energy Technology Data Exchange (ETDEWEB)

HOLT,ROBERT M.; WILSON,JOHN L.; GLASS JR.,ROBERT J.

2000-12-21

Hydraulic property measurements often rely on non-linear inversion models whose errors vary between samples. In non-linear physical measurement systems, bias can be directly quantified and removed using calibration standards. In hydrologic systems, field calibration is often infeasible and bias must be quantified indirectly. We use a Monte Carlo error analysis to indirectly quantify spatial bias in the saturated hydraulic conductivity, K{sub s}, and the exponential relative permeability parameter, {alpha}, estimated using a tension infiltrometer. Two types of observation error are considered, along with one inversion-model error resulting from poor contact between the instrument and the medium. Estimates of spatial statistics, including the mean, variance, and variogram-model parameters, show significant bias across a parameter space representative of poorly- to well-sorted silty sand to very coarse sand. When only observation errors are present, spatial statistics for both parameters are best estimated in materials with high hydraulic conductivity, like very coarse sand. When simple contact errors are included, the nature of the bias changes dramatically. Spatial statistics are poorly estimated, even in highly conductive materials. Conditions that permit accurate estimation of the statistics for one of the parameters prevent accurate estimation for the other; accurate regions for the two parameters do not overlap in parameter space. False cross-correlation between estimated parameters is created because estimates of K{sub s} also depend on estimates of {alpha} and both parameters are estimated from the same data.

On the Impact of Anomalous Noise Events on Road Traffic Noise Mapping in Urban and Suburban Environments.

Science.gov (United States)

Orga, Ferran; Alías, Francesc; Alsina-Pagès, Rosa Ma

2017-12-23

Noise pollution is a critical factor affecting public health, the relationship between road traffic noise (RTN) and several diseases in urban areas being especially disturbing. The Environmental Noise Directive 2002/49/EC and the CNOSSOS-EU framework are the main instruments of the European Union to identify and combat noise pollution, requiring Member States to compose and publish noise maps and noise management action plans every five years. Nowadays, the noise maps are starting to be tailored by means of Wireless Acoustic Sensor Networks (WASN). In order to exclusively monitor the impact of RTN on the well-being of citizens through WASN-based approaches, those noise sources unrelated to RTN denoted as Anomalous Noise Events (ANEs) should be removed from the noise map generation. This paper introduces an analysis methodology considering both Signal-to-Noise Ratio (SNR) and duration of ANEs to evaluate their impact on the A-weighted equivalent RTN level calculation for different integration times. The experiments conducted on 9 h of real-life data from the WASN-based DYNAMAP project show that both individual high-impact events and aggregated medium-impact events bias significantly the equivalent noise levels of the RTN map, making any derived study about public health impact inaccurate.

Coding space-time stimulus dynamics in auditory brain maps

Directory of Open Access Journals (Sweden)

Yunyan eWang

2014-04-01

Full Text Available Sensory maps are often distorted representations of the environment, where ethologically-important ranges are magnified. The implication of a biased representation extends beyond increased acuity for having more neurons dedicated to a certain range. Because neurons are functionally interconnected, non-uniform representations influence the processing of high-order features that rely on comparison across areas of the map. Among these features are time-dependent changes of the auditory scene generated by moving objects. How sensory representation affects high order processing can be approached in the map of auditory space of the owl’s midbrain, where locations in the front are over-represented. In this map, neurons are selective not only to location but also to location over time. The tuning to space over time leads to direction selectivity, which is also topographically organized. Across the population, neurons tuned to peripheral space are more selective to sounds moving into the front. The distribution of direction selectivity can be explained by spatial and temporal integration on the non-uniform map of space. Thus, the representation of space can induce biased computation of a second-order stimulus feature. This phenomenon is likely observed in other sensory maps and may be relevant for behavior.

New method for eliminating the statistical bias in highly turbulent flow measurements

International Nuclear Information System (INIS)

Nakao, S.I.; Terao, Y.; Hirata, K.I.; Kitakyushu Industrial Research Institute, Fukuoka, Japan)

1987-01-01

A simple method was developed for eliminating statistical bias which can be applied to highly turbulent flows with the sparse and nonuniform seeding conditions. Unlike the method proposed so far, a weighting function was determined based on the idea that the statistical bias could be eliminated if the asymmetric form of the probability density function of the velocity data were corrected. Moreover, the data more than three standard deviations away from the mean were discarded to remove the apparent turbulent intensity resulting from noise. The present method was applied to data obtained in the wake of a block, which provided local turbulent intensities up to about 120 percent, it was found to eliminate the statistical bias with high accuracy. 9 references

A New Source Biasing Approach in ADVANTG

International Nuclear Information System (INIS)

Bevill, Aaron M.; Mosher, Scott W.

2012-01-01

The ADVANTG code has been developed at Oak Ridge National Laboratory to generate biased sources and weight window maps for MCNP using the CADIS and FW-CADIS methods. In preparation for an upcoming RSICC release, a new approach for generating a biased source has been developed. This improvement streamlines user input and improves reliability. Previous versions of ADVANTG generated the biased source from ADVANTG input, writing an entirely new general fixed-source definition (SDEF). Because volumetric sources were translated into SDEF-format as a finite set of points, the user had to perform a convergence study to determine whether the number of source points used accurately represented the source region. Further, the large number of points that must be written in SDEF-format made the MCNP input and output files excessively long and difficult to debug. ADVANTG now reads SDEF-format distributions and generates corresponding source biasing cards, eliminating the need for a convergence study. Many problems of interest use complicated source regions that are defined using cell rejection. In cell rejection, the source distribution in space is defined using an arbitrarily complex cell and a simple bounding region. Source positions are sampled within the bounding region but accepted only if they fall within the cell; otherwise, the position is resampled entirely. When biasing in space is applied to sources that use rejection sampling, current versions of MCNP do not account for the rejection in setting the source weight of histories, resulting in an 'unfair game'. This problem was circumvented in previous versions of ADVANTG by translating volumetric sources into a finite set of points, which does not alter the mean history weight ((bar w)). To use biasing parameters without otherwise modifying the original cell-rejection SDEF-format source, ADVANTG users now apply a correction factor for (bar w) in post-processing. A stratified-random sampling approach in ADVANTG is under

Contingency bias in probability judgement may arise from ambiguity regarding additional causes.

Science.gov (United States)

Mitchell, Chris J; Griffiths, Oren; More, Pranjal; Lovibond, Peter F

2013-09-01

In laboratory contingency learning tasks, people usually give accurate estimates of the degree of contingency between a cue and an outcome. However, if they are asked to estimate the probability of the outcome in the presence of the cue, they tend to be biased by the probability of the outcome in the absence of the cue. This bias is often attributed to an automatic contingency detection mechanism, which is said to act via an excitatory associative link to activate the outcome representation at the time of testing. We conducted 3 experiments to test alternative accounts of contingency bias. Participants were exposed to the same outcome probability in the presence of the cue, but different outcome probabilities in the absence of the cue. Phrasing the test question in terms of frequency rather than probability and clarifying the test instructions reduced but did not eliminate contingency bias. However, removal of ambiguity regarding the presence of additional causes during the test phase did eliminate contingency bias. We conclude that contingency bias may be due to ambiguity in the test question, and therefore it does not require postulation of a separate associative link-based mechanism.

Normalization Approaches for Removing Systematic Biases Associated with Mass Spectrometry and Label-Free Proteomics

Energy Technology Data Exchange (ETDEWEB)

Callister, Stephen J.; Barry, Richard C.; Adkins, Joshua N.; Johnson, Ethan T.; Qian, Weijun; Webb-Robertson, Bobbie-Jo M.; Smith, Richard D.; Lipton, Mary S.

2006-02-01

Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS). Arbitrary abundances of peptides were obtained from three sample sets, including a standard protein sample, two Deinococcus radiodurans samples taken from different growth phases, and two mouse striatum samples from control and methamphetamine-stressed mice (strain C57BL/6). The selected normalization techniques were evaluated in both the absence and presence of biological variability by estimating extraneous variability prior to and following normalization. Prior to normalization, replicate runs from each sample set were observed to be statistically different, while following normalization replicate runs were no longer statistically different. Although all techniques reduced systematic bias, assigned ranks among the techniques revealed significant trends. For most LC-FTICR MS analyses, linear regression normalization ranked either first or second among the four techniques, suggesting that this technique was more generally suitable for reducing systematic biases.

Impacts of gate bias and its variation on gamma-ray irradiation resistance of SiC MOSFETs

Energy Technology Data Exchange (ETDEWEB)

Murata, Koichi; Mitomo, Satoshi; Matsuda, Takuma; Yokoseki, Takashi [Saitama University, Sakuraku (Japan); National Institutes for Quantum and Radiological Science and Technology (QST), Takasaki (Japan); Makino, Takahiro; Onoda, Shinobu; Takeyama, Akinori; Ohshima, Takeshi [National Institutes for Quantum and Radiological Science and Technology (QST), Takasaki (Japan); Okubo, Shuichi; Tanaka, Yuki; Kandori, Mikio; Yoshie, Toru [Sanken Electric Co., Ltd., Niiza, Saitama (Japan); Hijikata, Yasuto [Saitama University, Sakuraku (Japan)

2017-04-15

Gamma-ray irradiation into vertical type n-channel hexagonal (4H)-silicon carbide (SiC) metal-oxide-semiconductor field effect transistors (MOSFETs) was performed under various gate biases. The threshold voltage for the MOSFETs irradiated with a constant positive gate bias showed a large negative shift, and the shift slightly recovered above 100 kGy. For MOSFETs with non- and a negative constant biases, no significant change in threshold voltage, V{sub th}, was observed up to 400 kGy. By changing the gate bias from positive bias to either negative or non-bias, the V{sub th} significantly recovered from the large negative voltage shift induced by 50 kGy irradiation with positive gate bias after only 10 kGy irradiation with either negative or zero bias. It indicates that the positive charges generated in the gate oxide near the oxide-SiC interface due to irradiation were removed or recombined instantly by the irradiation under zero or negative biases. (copyright 2016 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

A Variational Approach to Simultaneous Image Segmentation and Bias Correction.

Science.gov (United States)

Zhang, Kaihua; Liu, Qingshan; Song, Huihui; Li, Xuelong

2015-08-01

This paper presents a novel variational approach for simultaneous estimation of bias field and segmentation of images with intensity inhomogeneity. We model intensity of inhomogeneous objects to be Gaussian distributed with different means and variances, and then introduce a sliding window to map the original image intensity onto another domain, where the intensity distribution of each object is still Gaussian but can be better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying the bias field with a piecewise constant signal within the sliding window. A maximum likelihood energy functional is then defined on each local region, which combines the bias field, the membership function of the object region, and the constant approximating the true signal from its corresponding object. The energy functional is then extended to the whole image domain by the Bayesian learning approach. An efficient iterative algorithm is proposed for energy minimization, via which the image segmentation and bias field correction are simultaneously achieved. Furthermore, the smoothness of the obtained optimal bias field is ensured by the normalized convolutions without extra cost. Experiments on real images demonstrated the superiority of the proposed algorithm to other state-of-the-art representative methods.

A simple technique investigating baseline heterogeneity helped to eliminate potential bias in meta-analyses.

Science.gov (United States)

Hicks, Amy; Fairhurst, Caroline; Torgerson, David J

2018-03-01

To perform a worked example of an approach that can be used to identify and remove potentially biased trials from meta-analyses via the analysis of baseline variables. True randomisation produces treatment groups that differ only by chance; therefore, a meta-analysis of a baseline measurement should produce no overall difference and zero heterogeneity. A meta-analysis from the British Medical Journal, known to contain significant heterogeneity and imbalance in baseline age, was chosen. Meta-analyses of baseline variables were performed and trials systematically removed, starting with those with the largest t-statistic, until the I 2 measure of heterogeneity became 0%, then the outcome meta-analysis repeated with only the remaining trials as a sensitivity check. We argue that heterogeneity in a meta-analysis of baseline variables should not exist, and therefore removing trials which contribute to heterogeneity from a meta-analysis will produce a more valid result. In our example none of the overall outcomes changed when studies contributing to heterogeneity were removed. We recommend routine use of this technique, using age and a second baseline variable predictive of outcome for the particular study chosen, to help eliminate potential bias in meta-analyses. Copyright © 2017 Elsevier Inc. All rights reserved.

Large-Scale Mapping of Carbon Stocks in Riparian Forests with Self-Organizing Maps and the k-Nearest-Neighbor Algorithm

Directory of Open Access Journals (Sweden)

Leonhard Suchenwirth

2014-07-01

Full Text Available Among the machine learning tools being used in recent years for environmental applications such as forestry, self-organizing maps (SOM and the k-nearest neighbor (kNN algorithm have been used successfully. We applied both methods for the mapping of organic carbon (Corg in riparian forests due to their considerably high carbon storage capacity. Despite the importance of floodplains for carbon sequestration, a sufficient scientific foundation for creating large-scale maps showing the spatial Corg distribution is still missing. We estimated organic carbon in a test site in the Danube Floodplain based on RapidEye remote sensing data and additional geodata. Accordingly, carbon distribution maps of vegetation, soil, and total Corg stocks were derived. Results were compared and statistically evaluated with terrestrial survey data for outcomes with pure remote sensing data and for the combination with additional geodata using bias and the Root Mean Square Error (RMSE. Results show that SOM and kNN approaches enable us to reproduce spatial patterns of riparian forest Corg stocks. While vegetation Corg has very high RMSEs, outcomes for soil and total Corg stocks are less biased with a lower RMSE, especially when remote sensing and additional geodata are conjointly applied. SOMs show similar percentages of RMSE to kNN estimations.

Compliance with removable orthodontic appliances.

Science.gov (United States)

Shah, Nirmal

2017-12-22

Data sourcesMedline via OVID, PubMed, Cochrane Central Register of Controlled Trials, Web of Science Core Collection, LILACS and BBO databases. Unpublished clinical trials accessed using ClinicalTrials.gov, National Research Register, ProQuest Dissertation and Thesis database.Study selectionTwo authors searched studies from inception until May 2016 without language restrictions. Quantitative and qualitative studies incorporating objective data on compliance with removable appliances, barriers to appliance wear compliance, and interventions to improve compliance were included.Data extraction and synthesisQuality of research was assessed using the Cochrane Collaboration's risk of bias tool, the risk of bias in non-randomised studies of interventions (ROBINS-I), and the mixed methods appraisal tool. Statistical heterogeneity was investigated by examining a graphic display of the estimated compliance levels in conjunction with 95% confidence intervals and quantified using the I-squared statistic. A weighted estimate of objective compliance levels for different appliances in relation to stipulated wear and self-reported levels was also calculated. Risk of publication bias was assessed using funnel plots. Meta-regression was undertaken to assess the relative effects of appliance type on compliance levels.ResultsTwenty-four studies met the inclusion criteria. Of these, 11 were included in the quantitative synthesis. The mean duration of objectively measured wear was considerably lower than stipulated wear time amongst all appliances. Headgear had the greatest discrepancy (5.81 hours, 95% confidence interval, 4.98, 6.64). Self-reported wear time was consistently higher than objectively measured wear time amongst all appliances. Headgear had the greatest discrepancy (5.02 hours, 95% confidence interval, 3.64, 6.40). Two studies found an increase in compliance with headgear and Hawley retainers when patients were aware of monitoring. Five studies found younger age groups to

Exploring Task Mappings on Heterogeneous MPSoCs using a Bias-Elitist Genetic Algorithm

NARCIS (Netherlands)

Quan, W.; Pimentel, A.D.

2014-01-01

Exploration of task mappings plays a crucial role in achieving high performance in heterogeneous multi-processor system-on-chip (MPSoC) platforms. The problem of optimally mapping a set of tasks onto a set of given heterogeneous processors for maximal throughput has been known, in general, to be

Deterministic hopping in a Josephson circuit described by a one-dimensional mapping

International Nuclear Information System (INIS)

Miracky, R.F.; Devoret, M.H.; Clarke, J.

1985-01-01

Analog simulations of the hopping noise of a current-biased Josephson tunnel junction shunted with an inductor in series with a resistor reveal a 1/ω spectral density over two decades of frequency ω for a narrow range of bias currents. The amplitude of the low-frequency part of the spectrum decreases when white noise, representing Nyquist noise in the resistor at a few degrees Kelvin, is added to the simulation. We explain the shape of the power spectrum and its dependence on bias current and added white noise in terms of a deterministic process, involving a one-dimensional mapping, that is analogous to that found in Pomeau-Manneville intermittency. Moreover, we are able to establish a detailed relationship between the origin of the mapping and the differential equation describing the dynamics of the system

Correction of gene expression data: Performance-dependency on inter-replicate and inter-treatment biases.

Science.gov (United States)

Darbani, Behrooz; Stewart, C Neal; Noeparvar, Shahin; Borg, Søren

2014-10-20

This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies. For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce an analytical approach to examine the suitability of correction methods by considering the inter-treatment bias as well as the inter-replicate variance, which allows use of the best correction method with minimum residual bias. Analyses of RNA sequencing and microarray data showed that the efficiencies of correction methods are influenced by the inter-treatment bias as well as the inter-replicate variance. Therefore, we recommend inspecting both of the bias sources in order to apply the most efficient correction method. As an alternative correction strategy, sequential application of different correction approaches is also advised. Copyright © 2014 Elsevier B.V. All rights reserved.

Statistical bias correction modelling for seasonal rainfall forecast for the case of Bali island

Science.gov (United States)

Lealdi, D.; Nurdiati, S.; Sopaheluwakan, A.

2018-04-01

Rainfall is an element of climate which is highly influential to the agricultural sector. Rain pattern and distribution highly determines the sustainability of agricultural activities. Therefore, information on rainfall is very useful for agriculture sector and farmers in anticipating the possibility of extreme events which often cause failures of agricultural production. This research aims to identify the biases from seasonal forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) rainfall forecast and to build a transfer function in order to correct the distribution biases as a new prediction model using quantile mapping approach. We apply this approach to the case of Bali Island, and as a result, the use of bias correction methods in correcting systematic biases from the model gives better results. The new prediction model obtained with this approach is better than ever. We found generally that during rainy season, the bias correction approach performs better than in dry season.

MAPPING THE SIMILARITIES OF SPECTRA: GLOBAL AND LOCALLY-BIASED APPROACHES TO SDSS GALAXIES

Energy Technology Data Exchange (ETDEWEB)

Lawlor, David [Statistical and Applied Mathematical Sciences Institute (United States); Budavári, Tamás [Dept. of Applied Mathematics and Statistics, The Johns Hopkins University (United States); Mahoney, Michael W. [International Computer Science Institute (United States)

2016-12-10

We present a novel approach to studying the diversity of galaxies. It is based on a novel spectral graph technique, that of locally-biased semi-supervised eigenvectors . Our method introduces new coordinates that summarize an entire spectrum, similar to but going well beyond the widely used Principal Component Analysis (PCA). Unlike PCA, however, this technique does not assume that the Euclidean distance between galaxy spectra is a good global measure of similarity. Instead, we relax that condition to only the most similar spectra, and we show that doing so yields more reliable results for many astronomical questions of interest. The global variant of our approach can identify very finely numerous astronomical phenomena of interest. The locally-biased variants of our basic approach enable us to explore subtle trends around a set of chosen objects. The power of the method is demonstrated in the Sloan Digital Sky Survey Main Galaxy Sample, by illustrating that the derived spectral coordinates carry an unprecedented amount of information.

Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxies

Science.gov (United States)

Lawlor, David; Budavári, Tamás; Mahoney, Michael W.

2016-12-01

We present a novel approach to studying the diversity of galaxies. It is based on a novel spectral graph technique, that of locally-biased semi-supervised eigenvectors. Our method introduces new coordinates that summarize an entire spectrum, similar to but going well beyond the widely used Principal Component Analysis (PCA). Unlike PCA, however, this technique does not assume that the Euclidean distance between galaxy spectra is a good global measure of similarity. Instead, we relax that condition to only the most similar spectra, and we show that doing so yields more reliable results for many astronomical questions of interest. The global variant of our approach can identify very finely numerous astronomical phenomena of interest. The locally-biased variants of our basic approach enable us to explore subtle trends around a set of chosen objects. The power of the method is demonstrated in the Sloan Digital Sky Survey Main Galaxy Sample, by illustrating that the derived spectral coordinates carry an unprecedented amount of information.

MAPPING THE SIMILARITIES OF SPECTRA: GLOBAL AND LOCALLY-BIASED APPROACHES TO SDSS GALAXIES

International Nuclear Information System (INIS)

Lawlor, David; Budavári, Tamás; Mahoney, Michael W.

2016-01-01

We present a novel approach to studying the diversity of galaxies. It is based on a novel spectral graph technique, that of locally-biased semi-supervised eigenvectors . Our method introduces new coordinates that summarize an entire spectrum, similar to but going well beyond the widely used Principal Component Analysis (PCA). Unlike PCA, however, this technique does not assume that the Euclidean distance between galaxy spectra is a good global measure of similarity. Instead, we relax that condition to only the most similar spectra, and we show that doing so yields more reliable results for many astronomical questions of interest. The global variant of our approach can identify very finely numerous astronomical phenomena of interest. The locally-biased variants of our basic approach enable us to explore subtle trends around a set of chosen objects. The power of the method is demonstrated in the Sloan Digital Sky Survey Main Galaxy Sample, by illustrating that the derived spectral coordinates carry an unprecedented amount of information.

Modeling bias and variation in the stochastic processes of small RNA sequencing.

Science.gov (United States)

Argyropoulos, Christos; Etheridge, Alton; Sakhanenko, Nikita; Galas, David

2017-06-20

The use of RNA-seq as the preferred method for the discovery and validation of small RNA biomarkers has been hindered by high quantitative variability and biased sequence counts. In this paper we develop a statistical model for sequence counts that accounts for ligase bias and stochastic variation in sequence counts. This model implies a linear quadratic relation between the mean and variance of sequence counts. Using a large number of sequencing datasets, we demonstrate how one can use the generalized additive models for location, scale and shape (GAMLSS) distributional regression framework to calculate and apply empirical correction factors for ligase bias. Bias correction could remove more than 40% of the bias for miRNAs. Empirical bias correction factors appear to be nearly constant over at least one and up to four orders of magnitude of total RNA input and independent of sample composition. Using synthetic mixes of known composition, we show that the GAMLSS approach can analyze differential expression with greater accuracy, higher sensitivity and specificity than six existing algorithms (DESeq2, edgeR, EBSeq, limma, DSS, voom) for the analysis of small RNA-seq data. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

MARRT: Medial Axis biased rapidly-exploring random trees

KAUST Repository

Denny, Jory

2014-05-01

© 2014 IEEE. Motion planning is a difficult and widely studied problem in robotics. Current research aims not only to find feasible paths, but to ensure paths have certain properties, e.g., shortest or safest paths. This is difficult for current state-of-the-art sampling-based techniques as they typically focus on simply finding any path. Despite this difficulty, sampling-based techniques have shown great success in planning for a wide range of applications. Among such planners, Rapidly-Exploring Random Trees (RRTs) search the planning space by biasing exploration toward unexplored regions. This paper introduces a novel RRT variant, Medial Axis RRT (MARRT), which biases tree exploration to the medial axis of free space by pushing all configurations from expansion steps towards the medial axis. We prove that this biasing increases the tree\\'s clearance from obstacles. Improving obstacle clearance is useful where path safety is important, e.g., path planning for robots performing tasks in close proximity to the elderly. Finally, we experimentally analyze MARRT, emphasizing its ability to effectively map difficult passages while increasing obstacle clearance, and compare it to contemporary RRT techniques.

Counteracting estimation bias and social influence to improve the wisdom of crowds.

Science.gov (United States)

Kao, Albert B; Berdahl, Andrew M; Hartnett, Andrew T; Lutz, Matthew J; Bak-Coleman, Joseph B; Ioannou, Christos C; Giam, Xingli; Couzin, Iain D

2018-04-01

Aggregating multiple non-expert opinions into a collective estimate can improve accuracy across many contexts. However, two sources of error can diminish collective wisdom: individual estimation biases and information sharing between individuals. Here, we measure individual biases and social influence rules in multiple experiments involving hundreds of individuals performing a classic numerosity estimation task. We first investigate how existing aggregation methods, such as calculating the arithmetic mean or the median, are influenced by these sources of error. We show that the mean tends to overestimate, and the median underestimate, the true value for a wide range of numerosities. Quantifying estimation bias, and mapping individual bias to collective bias, allows us to develop and validate three new aggregation measures that effectively counter sources of collective estimation error. In addition, we present results from a further experiment that quantifies the social influence rules that individuals employ when incorporating personal estimates with social information. We show that the corrected mean is remarkably robust to social influence, retaining high accuracy in the presence or absence of social influence, across numerosities and across different methods for averaging social information. Using knowledge of estimation biases and social influence rules may therefore be an inexpensive and general strategy to improve the wisdom of crowds. © 2018 The Author(s).

Biased Dropout and Crossmap Dropout: Learning towards effective Dropout regularization in convolutional neural network.

Science.gov (United States)

Poernomo, Alvin; Kang, Dae-Ki

2018-08-01

Training a deep neural network with a large number of parameters often leads to overfitting problem. Recently, Dropout has been introduced as a simple, yet effective regularization approach to combat overfitting in such models. Although Dropout has shown remarkable results on many deep neural network cases, its actual effect on CNN has not been thoroughly explored. Moreover, training a Dropout model will significantly increase the training time as it takes longer time to converge than a non-Dropout model with the same architecture. To deal with these issues, we address Biased Dropout and Crossmap Dropout, two novel approaches of Dropout extension based on the behavior of hidden units in CNN model. Biased Dropout divides the hidden units in a certain layer into two groups based on their magnitude and applies different Dropout rate to each group appropriately. Hidden units with higher activation value, which give more contributions to the network final performance, will be retained by a lower Dropout rate, while units with lower activation value will be exposed to a higher Dropout rate to compensate the previous part. The second approach is Crossmap Dropout, which is an extension of the regular Dropout in convolution layer. Each feature map in a convolution layer has a strong correlation between each other, particularly in every identical pixel location in each feature map. Crossmap Dropout tries to maintain this important correlation yet at the same time break the correlation between each adjacent pixel with respect to all feature maps by applying the same Dropout mask to all feature maps, so that all pixels or units in equivalent positions in each feature map will be either dropped or active during training. Our experiment with various benchmark datasets shows that our approaches provide better generalization than the regular Dropout. Moreover, our Biased Dropout takes faster time to converge during training phase, suggesting that assigning noise appropriately in

A COSMIC MICROWAVE BACKGROUND LENSING MASS MAP AND ITS CORRELATION WITH THE COSMIC INFRARED BACKGROUND

Energy Technology Data Exchange (ETDEWEB)

Holder, G. P.; De Haan, T.; Dobbs, M. A.; Dudley, J. [Department of Physics, McGill University, Montreal, Quebec H3A 2T8 (Canada); Viero, M. P.; Bock, J. [California Institute of Technology, Pasadena, CA 91125 (United States); Zahn, O. [Berkeley Center for Cosmological Physics, Department of Physics, University of California, and Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Aird, K. A. [University of Chicago, Chicago, IL 60637 (United States); Benson, B. A.; Bhattacharya, S.; Bleem, L. E.; Carlstrom, J. E.; Chang, C. L.; Crawford, T. M.; Crites, A. T. [Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637 (United States); Brodwin, M. [Department of Physics and Astronomy, University of Missouri, Kansas City, MO 64110 (United States); Cho, H-M. [NIST Quantum Devices Group, Boulder, CO 80305 (United States); Conley, A. [Center for Astrophysics and Space Astronomy, University of Colorado, Boulder, CO 80309 (United States); George, E. M. [Department of Physics, University of California, Berkeley, CA 94720 (United States); Halverson, N. W. [Department of Astrophysical and Planetary Sciences and Department of Physics, University of Colorado, Boulder, CO 80309 (United States); and others

2013-07-01

We use a temperature map of the cosmic microwave background (CMB) obtained using the South Pole Telescope at 150 GHz to construct a map of the gravitational convergence to z {approx} 1100, revealing the fluctuations in the projected mass density. This map shows individual features that are significant at the {approx}4{sigma} level, providing the first image of CMB lensing convergence. We cross-correlate this map with Herschel/SPIRE maps covering 90 deg{sup 2} at wavelengths of 500, 350, and 250 {mu}m. We show that these submillimeter (submm) wavelength maps are strongly correlated with the lensing convergence map, with detection significances in each of the three submm bands ranging from 6.7{sigma} to 8.8{sigma}. We fit the measurement of the cross power spectrum assuming a simple constant bias model and infer bias factors of b = 1.3-1.8, with a statistical uncertainty of 15%, depending on the assumed model for the redshift distribution of the dusty galaxies that are contributing to the Herschel/SPIRE maps.

Cognitive debiasing 1: origins of bias and theory of debiasing.

Science.gov (United States)

Croskerry, Pat; Singhal, Geeta; Mamede, Sílvia

2013-10-01

Numerous studies have shown that diagnostic failure depends upon a variety of factors. Psychological factors are fundamental in influencing the cognitive performance of the decision maker. In this first of two papers, we discuss the basics of reasoning and the Dual Process Theory (DPT) of decision making. The general properties of the DPT model, as it applies to diagnostic reasoning, are reviewed. A variety of cognitive and affective biases are known to compromise the decision-making process. They mostly appear to originate in the fast intuitive processes of Type 1 that dominate (or drive) decision making. Type 1 processes work well most of the time but they may open the door for biases. Removing or at least mitigating these biases would appear to be an important goal. We will also review the origins of biases. The consensus is that there are two major sources: innate, hard-wired biases that developed in our evolutionary past, and acquired biases established in the course of development and within our working environments. Both are associated with abbreviated decision making in the form of heuristics. Other work suggests that ambient and contextual factors may create high risk situations that dispose decision makers to particular biases. Fatigue, sleep deprivation and cognitive overload appear to be important determinants. The theoretical basis of several approaches towards debiasing is then discussed. All share a common feature that involves a deliberate decoupling from Type 1 intuitive processing and moving to Type 2 analytical processing so that eventually unexamined intuitive judgments can be submitted to verification. This decoupling step appears to be the critical feature of cognitive and affective debiasing.

Mis-estimation and bias of hyperpolarized apparent diffusion coefficient measurements due to slice profile effects.

Science.gov (United States)

Gordon, Jeremy W; Milshteyn, Eugene; Marco-Rius, Irene; Ohliger, Michael; Vigneron, Daniel B; Larson, Peder E Z

2017-09-01

The purpose of this work was to explore the impact of slice profile effects on apparent diffusion coefficient (ADC) mapping of hyperpolarized (HP) substrates. Slice profile effects were simulated using a Gaussian radiofrequency (RF) pulse with a variety of flip angle schedules and b-value ordering schemes. A long T 1 water phantom was used to validate the simulation results, and ADC mapping of HP [ 13 C, 15 N 2 ]urea was performed on the murine liver to assess these effects in vivo. Slice profile effects result in excess signal after repeated RF pulses, causing bias in HP measurements. The largest error occurs for metabolites with small ADCs, resulting in up to 10-fold overestimation for metabolites that are in more-restricted environments. A mixed b-value scheme substantially reduces this bias, whereas scaling the slice-select gradient can mitigate it completely. In vivo, the liver ADC of hyperpolarized [ 13 C, 15 N 2 ]urea is nearly 70% lower (0.99 ± 0.22 vs 1.69 ± 0.21 × 10 -3 mm 2 /s) when slice-select gradient scaling is used. Slice profile effects can lead to bias in HP ADC measurements. A mixed b-value ordering scheme can reduce this bias compared to sequential b-value ordering. Slice-select gradient scaling can also correct for this deviation, minimizing bias and providing more-precise ADC measurements of HP substrates. Magn Reson Med 78:1087-1092, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

The Extracellular Surface of the GLP-1 Receptor Is a Molecular Trigger for Biased Agonism.

Science.gov (United States)

Wootten, Denise; Reynolds, Christopher A; Smith, Kevin J; Mobarec, Juan C; Koole, Cassandra; Savage, Emilia E; Pabreja, Kavita; Simms, John; Sridhar, Rohan; Furness, Sebastian G B; Liu, Mengjie; Thompson, Philip E; Miller, Laurence J; Christopoulos, Arthur; Sexton, Patrick M

2016-06-16

Ligand-directed signal bias offers opportunities for sculpting molecular events, with the promise of better, safer therapeutics. Critical to the exploitation of signal bias is an understanding of the molecular events coupling ligand binding to intracellular signaling. Activation of class B G protein-coupled receptors is driven by interaction of the peptide N terminus with the receptor core. To understand how this drives signaling, we have used advanced analytical methods that enable separation of effects on pathway-specific signaling from those that modify agonist affinity and mapped the functional consequence of receptor modification onto three-dimensional models of a receptor-ligand complex. This yields molecular insights into the initiation of receptor activation and the mechanistic basis for biased agonism. Our data reveal that peptide agonists can engage different elements of the receptor extracellular face to achieve effector coupling and biased signaling providing a foundation for rational design of biased agonists. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Sympathetic bias.

Science.gov (United States)

Levy, David M; Peart, Sandra J

2008-06-01

We wish to deal with investigator bias in a statistical context. We sketch how a textbook solution to the problem of "outliers" which avoids one sort of investigator bias, creates the temptation for another sort. We write down a model of the approbation seeking statistician who is tempted by sympathy for client to violate the disciplinary standards. We give a simple account of one context in which we might expect investigator bias to flourish. Finally, we offer tentative suggestions to deal with the problem of investigator bias which follow from our account. As we have given a very sparse and stylized account of investigator bias, we ask what might be done to overcome this limitation.

Bias modification training can alter approach bias and chocolate consumption.

Science.gov (United States)

Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika

2016-01-01

Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.

Combination of biased forecasts: Bias correction or bias based weights?

OpenAIRE

Wenzel, Thomas

1999-01-01

Most of the literature on combination of forecasts deals with the assumption of unbiased individual forecasts. Here, we consider the case of biased forecasts and discuss two different combination techniques resulting in an unbiased forecast. On the one hand we correct the individual forecasts, and on the other we calculate bias based weights. A simulation study gives some insight in the situations where we should use the different methods.

Bias atlases for segmentation-based PET attenuation correction using PET-CT and MR.

Science.gov (United States)

Ouyang, Jinsong; Chun, Se Young; Petibon, Yoann; Bonab, Ali A; Alpert, Nathaniel; Fakhri, Georges El

2013-10-01

This study was to obtain voxel-wise PET accuracy and precision using tissue-segmentation for attenuation correction. We applied multiple thresholds to the CTs of 23 patients to classify tissues. For six of the 23 patients, MR images were also acquired. The MR fat/in-phase ratio images were used for fat segmentation. Segmented tissue classes were used to create attenuation maps, which were used for attenuation correction in PET reconstruction. PET bias images were then computed using the PET reconstructed with the original CT as the reference. We registered the CTs for all the patients and transformed the corresponding bias images accordingly. We then obtained the mean and standard deviation bias atlas using all the registered bias images. Our CT-based study shows that four-class segmentation (air, lungs, fat, other tissues), which is available on most PET-MR scanners, yields 15.1%, 4.1%, 6.6%, and 12.9% RMSE bias in lungs, fat, non-fat soft-tissues, and bones, respectively. An accurate fat identification is achievable using fat/in-phase MR images. Furthermore, we have found that three-class segmentation (air, lungs, other tissues) yields less than 5% standard deviation of bias within the heart, liver, and kidneys. This implies that three-class segmentation can be sufficient to achieve small variation of bias for imaging these three organs. Finally, we have found that inter- and intra-patient lung density variations contribute almost equally to the overall standard deviation of bias within the lungs.

Estimation bias and bias correction in reduced rank autoregressions

DEFF Research Database (Denmark)

Nielsen, Heino Bohn

2017-01-01

This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...

Practical estimate of gradient nonlinearity for implementation of apparent diffusion coefficient bias correction.

Science.gov (United States)

Malkyarenko, Dariya I; Chenevert, Thomas L

2014-12-01

To describe an efficient procedure to empirically characterize gradient nonlinearity and correct for the corresponding apparent diffusion coefficient (ADC) bias on a clinical magnetic resonance imaging (MRI) scanner. Spatial nonlinearity scalars for individual gradient coils along superior and right directions were estimated via diffusion measurements of an isotropicic e-water phantom. Digital nonlinearity model from an independent scanner, described in the literature, was rescaled by system-specific scalars to approximate 3D bias correction maps. Correction efficacy was assessed by comparison to unbiased ADC values measured at isocenter. Empirically estimated nonlinearity scalars were confirmed by geometric distortion measurements of a regular grid phantom. The applied nonlinearity correction for arbitrarily oriented diffusion gradients reduced ADC bias from 20% down to 2% at clinically relevant offsets both for isotropic and anisotropic media. Identical performance was achieved using either corrected diffusion-weighted imaging (DWI) intensities or corrected b-values for each direction in brain and ice-water. Direction-average trace image correction was adequate only for isotropic medium. Empiric scalar adjustment of an independent gradient nonlinearity model adequately described DWI bias for a clinical scanner. Observed efficiency of implemented ADC bias correction quantitatively agreed with previous theoretical predictions and numerical simulations. The described procedure provides an independent benchmark for nonlinearity bias correction of clinical MRI scanners.

Bias-correction of CORDEX-MENA projections using the Distribution Based Scaling method

Science.gov (United States)

Bosshard, Thomas; Yang, Wei; Sjökvist, Elin; Arheimer, Berit; Graham, L. Phil

2014-05-01

Within the Regional Initiative for the Assessment of the Impact of Climate Change on Water Resources and Socio-Economic Vulnerability in the Arab Region (RICCAR) lead by UN ESCWA, CORDEX RCM projections for the Middle East Northern Africa (MENA) domain are used to drive hydrological impacts models. Bias-correction of newly available CORDEX-MENA projections is a central part of this project. In this study, the distribution based scaling (DBS) method has been applied to 6 regional climate model projections driven by 2 RCP emission scenarios. The DBS method uses a quantile mapping approach and features a conditional temperature correction dependent on the wet/dry state in the climate model data. The CORDEX-MENA domain is particularly challenging for bias-correction as it spans very diverse climates showing pronounced dry and wet seasons. Results show that the regional climate models simulate too low temperatures and often have a displaced rainfall band compared to WATCH ERA-Interim forcing data in the reference period 1979-2008. DBS is able to correct the temperature biases as well as some aspects of the precipitation biases. Special focus is given to the analysis of the influence of the dry-frequency bias (i.e. climate models simulating too few rain days) on the bias-corrected projections and on the modification of the climate change signal by the DBS method.

Causes of model dry and warm bias over central U.S. and impact on climate projections.

Science.gov (United States)

Lin, Yanluan; Dong, Wenhao; Zhang, Minghua; Xie, Yuanyu; Xue, Wei; Huang, Jianbin; Luo, Yong

2017-10-12

Climate models show a conspicuous summer warm and dry bias over the central United States. Using results from 19 climate models in the Coupled Model Intercomparison Project Phase 5 (CMIP5), we report a persistent dependence of warm bias on dry bias with the precipitation deficit leading the warm bias over this region. The precipitation deficit is associated with the widespread failure of models in capturing strong rainfall events in summer over the central U.S. A robust linear relationship between the projected warming and the present-day warm bias enables us to empirically correct future temperature projections. By the end of the 21st century under the RCP8.5 scenario, the corrections substantially narrow the intermodel spread of the projections and reduce the projected temperature by 2.5 K, resulting mainly from the removal of the warm bias. Instead of a sharp decrease, after this correction the projected precipitation is nearly neutral for all scenarios.Climate models repeatedly show a warm and dry bias over the central United States, but the origin of this bias remains unclear. Here the authors associate this bias to precipitation deficits in models and after applying a correction, projected precipitation in this region shows no significant changes.

Use of bird carcass removals by urban scavengers to adjust bird-window collision estimates

Directory of Open Access Journals (Sweden)

Justine A. Kummer

2016-12-01

Full Text Available Carcass removal by scavengers has been identified as one of the largest biases in estimating bird mortality from anthropogenic sources. Only two studies have examined carcass removal by scavengers in an urban environment, and previous estimates of bird-window collision mortality at houses have relied on carcass removal rates from wind turbine studies. We placed a bird carcass and time-lapse camera at 44 houses in Edmonton, Alberta. In total, 166 7-day trials were conducted throughout 2015. Time-to-event (survival analysis was used to identify covariates that affected removal. The carcass removal rate was determined for use in estimating the number of birds killed from bird-window collisions at houses in Alberta. In total, 67.5% of carcasses were removed. The date the carcass was placed, the year the house was built, and the level of development within 50 m of the house were the covariates that had the largest effect on carcass removal. In calculating our removal rate, the number of detected carcasses in the first 24 hours was adjusted by 1.47 to account for removal by scavengers. Previously collected citizen science data were used to create an estimate of 957,440 bird deaths each year in Alberta as a result of bird-window collisions with houses. This number is based on the most detailed bird-window collision study at houses to date and a carcass removal study conducted in the same area. Similar localized studies across Canada will need to be completed to reduce the biases that exist with the previous bird-window collision mortality estimate for houses in Canada.

Real-space Mapping of Surface Trap States in CIGSe Nanocrystals using 4D Electron Microscopy

KAUST Repository

Bose, Riya

2016-05-26

Surface trap states in semiconductor copper indium gallium selenide nanocrystals (NCs) which serve as undesirable channels for non-radiative carrier recombination, remain a great challenge impeding the development of solar and optoelectronics devices based on these NCs. In order to design efficient passivation techniques to minimize these trap states, a precise knowledge about the charge carrier dynamics on the NCs surface is essential. However, selective mapping of surface traps requires capabilities beyond the reach of conventional laser spectroscopy and static electron microscopy; it can only be accessed by using a one-of-a-kind, second-generation four-dimensional scanning ultrafast electron microscope (4D S-UEM) with sub-picosecond temporal and nanometer spatial resolutions. Here, we precisely map the surface charge carrier dynamics of copper indium gallium selenide NCs before and after surface passivation in real space and time using S-UEM. The time-resolved snapshots clearly demonstrate that the density of the trap states is significantly reduced after zinc sulfide (ZnS) shelling. Furthermore, removal of trap states and elongation of carrier lifetime are confirmed by the increased photocurrent of the self-biased photodetector fabricated using the shelled NCs.

Real-space Mapping of Surface Trap States in CIGSe Nanocrystals using 4D Electron Microscopy

KAUST Repository

Bose, Riya; Bera, Ashok; Parida, Manas R.; Adhikari, Aniruddha; Shaheen, Basamat; Alarousu, Erkki; Sun, Jingya; Wu, Tao; Bakr, Osman; Mohammed, Omar F.

2016-01-01

Surface trap states in semiconductor copper indium gallium selenide nanocrystals (NCs) which serve as undesirable channels for non-radiative carrier recombination, remain a great challenge impeding the development of solar and optoelectronics devices based on these NCs. In order to design efficient passivation techniques to minimize these trap states, a precise knowledge about the charge carrier dynamics on the NCs surface is essential. However, selective mapping of surface traps requires capabilities beyond the reach of conventional laser spectroscopy and static electron microscopy; it can only be accessed by using a one-of-a-kind, second-generation four-dimensional scanning ultrafast electron microscope (4D S-UEM) with sub-picosecond temporal and nanometer spatial resolutions. Here, we precisely map the surface charge carrier dynamics of copper indium gallium selenide NCs before and after surface passivation in real space and time using S-UEM. The time-resolved snapshots clearly demonstrate that the density of the trap states is significantly reduced after zinc sulfide (ZnS) shelling. Furthermore, removal of trap states and elongation of carrier lifetime are confirmed by the increased photocurrent of the self-biased photodetector fabricated using the shelled NCs.

GALAXY BIAS AND ITS EFFECTS ON THE BARYON ACOUSTIC OSCILLATION MEASUREMENTS

International Nuclear Information System (INIS)

Mehta, Kushal T.; Eckel, Jonathan; Eisenstein, Daniel J.; Metchnik, Marc; Pinto, Philip; Xu Xiaoying; Seo, Hee-Jong

2011-01-01

The baryon acoustic oscillation (BAO) feature in the clustering of matter in the universe serves as a robust standard ruler and hence can be used to map the expansion history of the universe. We use high force resolution simulations to analyze the effects of galaxy bias on the measurements of the BAO signal. We apply a variety of Halo Occupation Distributions (HODs) and produce biased mass tracers to mimic different galaxy populations. We investigate whether galaxy bias changes the nonlinear shifts on the acoustic scale relative to the underlying dark matter distribution presented by Seo et al. For the less biased HOD models (b 3) show a shift at moderate significance (0.79% ± 0.31% for the most extreme case). We test the one-step reconstruction technique introduced by Eisenstein et al. in the case of realistic galaxy bias and shot noise. The reconstruction scheme increases the correlation between the initial and final (z = 1) density fields, achieving an equivalent level of correlation at nearly twice the wavenumber after reconstruction. Reconstruction reduces the shifts and errors on the shifts. We find that after reconstruction the shifts from the galaxy cases and the dark matter case are consistent with each other and with no shift. The 1σ systematic errors on the distance measurements inferred from our BAO measurements with various HODs after reconstruction are about 0.07%-0.15%.

Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange

Science.gov (United States)

Takaishi, Tetsuya

2018-06-01

The realized stochastic volatility model has been introduced to estimate more accurate volatility by using both daily returns and realized volatility. The main advantage of the model is that no special bias-correction factor for the realized volatility is required a priori. Instead, the model introduces a bias-correction parameter responsible for the bias hidden in realized volatility. We empirically investigate the bias-correction parameter for realized volatilities calculated at various sampling frequencies for six stocks on the Tokyo Stock Exchange, and then show that the dynamic behavior of the bias-correction parameter as a function of sampling frequency is qualitatively similar to that of the Hansen-Lunde bias-correction factor although their values are substantially different. Under the stochastic diffusion assumption of the return dynamics, we investigate the accuracy of estimated volatilities by examining the standardized returns. We find that while the moments of the standardized returns from low-frequency realized volatilities are consistent with the expectation from the Gaussian variables, the deviation from the expectation becomes considerably large at high frequencies. This indicates that the realized stochastic volatility model itself cannot completely remove bias at high frequencies.

A method for the quantification of biased signalling at constitutively active receptors.

Science.gov (United States)

Hall, David A; Giraldo, Jesús

2018-06-01

Biased agonism, the ability of an agonist to differentially activate one of several signal transduction pathways when acting at a given receptor, is an increasingly recognized phenomenon at many receptors. The Black and Leff operational model lacks a way to describe constitutive receptor activity and hence inverse agonism. Thus, it is impossible to analyse the biased signalling of inverse agonists using this model. In this theoretical work, we develop and illustrate methods for the analysis of biased inverse agonism. Methods were derived for quantifying biased signalling in systems that demonstrate constitutive activity using the modified operational model proposed by Slack and Hall. The methods were illustrated using Monte Carlo simulations. The Monte Carlo simulations demonstrated that, with an appropriate experimental design, the model parameters are 'identifiable'. The method is consistent with methods based on the measurement of intrinsic relative activity (RA i ) (ΔΔlogR or ΔΔlog(τ/K a )) proposed by Ehlert and Kenakin and their co-workers but has some advantages. In particular, it allows the quantification of ligand bias independently of 'system bias' removing the requirement to normalize to a standard ligand. In systems with constitutive activity, the Slack and Hall model provides methods for quantifying the absolute bias of agonists and inverse agonists. This provides an alternative to methods based on RA i and is complementary to the ΔΔlog(τ/K a ) method of Kenakin et al. in systems where use of that method is inappropriate due to the presence of constitutive activity. © 2018 The British Pharmacological Society.

Bias correction method for climate change impact assessment at a basin scale

Science.gov (United States)

Nyunt, C.; Jaranilla-sanchez, P. A.; Yamamoto, A.; Nemoto, T.; Kitsuregawa, M.; Koike, T.

2012-12-01

. In this study, the lowest value of AMS of observed is selected as threshold and simultaneously same frequency is considered as extremes in corresponding GCM gridded series. After fitting to GP distribution, bias corrected GCM extreme is found by using the inverse function of observed extremes. The results show it can remove bias effectively. For projected climate, the same transfer function between historical observed and GCM was applied. Moreover, frequency analysis of maximum extreme intensity estimation was done for validation and then approximate for near future by using identical function as past. To fix the error in the number of no rain days of GCM, ranking order statistics is used and define in GCM same as the frequency of wet days in observed station. After this rank, GCM output will be zero and identify same threshold for future projection. Normal rainfall is classified as between threshold of extreme and no rain day. We assume monthly normal rainfall follow gamma distribution. Then, we mapped the CDF of GCM normal rainfall to station's one in each month and bias corrected rainfall is available. In summary, bias of GCM have been addressed efficiently and validated at point scale by seasonal climatology and at all stations for evaluating downscaled rainfall performance. The results show bias corrected and downscaled scheme is good enough for climate impact study.

Quantification of both the area-at-risk and acute myocardial infarct size in ST-segment elevation myocardial infarction using T1-mapping.

Science.gov (United States)

Bulluck, Heerajnarain; Hammond-Haley, Matthew; Fontana, Marianna; Knight, Daniel S; Sirker, Alex; Herrey, Anna S; Manisty, Charlotte; Kellman, Peter; Moon, James C; Hausenloy, Derek J

2017-08-01

A comprehensive cardiovascular magnetic resonance (CMR) in reperfused ST-segment myocardial infarction (STEMI) patients can be challenging to perform and can be time-consuming. We aimed to investigate whether native T1-mapping can accurately delineate the edema-based area-at-risk (AAR) and post-contrast T1-mapping and synthetic late gadolinium (LGE) images can quantify MI size at 1.5 T. Conventional LGE imaging and T2-mapping could then be omitted, thereby shortening the scan duration. Twenty-eight STEMI patients underwent a CMR scan at 1.5 T, 3 ± 1 days following primary percutaneous coronary intervention. The AAR was quantified using both native T1 and T2-mapping. MI size was quantified using conventional LGE, post-contrast T1-mapping and synthetic magnitude-reconstructed inversion recovery (MagIR) LGE and synthetic phase-sensitive inversion recovery (PSIR) LGE, derived from the post-contrast T1 maps. Native T1-mapping performed as well as T2-mapping in delineating the AAR (41.6 ± 11.9% of the left ventricle [% LV] versus 41.7 ± 12.2% LV, P = 0.72; R 2 0.97; ICC 0.986 (0.969-0.993); bias -0.1 ± 4.2% LV). There were excellent correlation and inter-method agreement with no bias, between MI size by conventional LGE, synthetic MagIR LGE (bias 0.2 ± 2.2%LV, P = 0.35), synthetic PSIR LGE (bias 0.4 ± 2.2% LV, P = 0.060) and post-contrast T1-mapping (bias 0.3 ± 1.8% LV, P = 0.10). The mean scan duration was 58 ± 4 min. Not performing T2 mapping (6 ± 1 min) and conventional LGE (10 ± 1 min) would shorten the CMR study by 15-20 min. T1-mapping can accurately quantify both the edema-based AAR (using native T1 maps) and acute MI size (using post-contrast T1 maps) in STEMI patients without major cardiovascular risk factors. This approach would shorten the duration of a comprehensive CMR study without significantly compromising on data acquisition and would obviate the need to perform T2 maps and LGE imaging.

A large-area, spatially continuous assessment of land cover map error and its impact on downstream analyses.

Science.gov (United States)

Estes, Lyndon; Chen, Peng; Debats, Stephanie; Evans, Tom; Ferreira, Stefanus; Kuemmerle, Tobias; Ragazzo, Gabrielle; Sheffield, Justin; Wolf, Adam; Wood, Eric; Caylor, Kelly

2018-01-01

Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high-resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel-wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative "downstream" (map-based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps' spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ∼45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National-scale maps derived from higher-resolution imagery were most accurate, followed by multi-map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland-adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%-500% greater than in input cropland maps, but ∼40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land

Geographic bias related to geocoding in epidemiologic studies

Directory of Open Access Journals (Sweden)

Siadaty Mir

2005-11-01

Full Text Available Abstract Background This article describes geographic bias in GIS analyses with unrepresentative data owing to missing geocodes, using as an example a spatial analysis of prostate cancer incidence among whites and African Americans in Virginia, 1990–1999. Statistical tests for clustering were performed and such clusters mapped. The patterns of missing census tract identifiers for the cases were examined by generalized linear regression models. Results The county of residency for all cases was known, and 26,338 (74% of these cases were geocoded successfully to census tracts. Cluster maps showed patterns that appeared markedly different, depending upon whether one used all cases or those geocoded to the census tract. Multivariate regression analysis showed that, in the most rural counties (where the missing data were concentrated, the percent of a county's population over age 64 and with less than a high school education were both independently associated with a higher percent of missing geocodes. Conclusion We found statistically significant pattern differences resulting from spatially non-random differences in geocoding completeness across Virginia. Appropriate interpretation of maps, therefore, requires an understanding of this phenomenon, which we call "cartographic confounding."

An associative model of adaptive inference for learning word-referent mappings.

Science.gov (United States)

Kachergis, George; Yu, Chen; Shiffrin, Richard M

2012-04-01

People can learn word-referent pairs over a short series of individually ambiguous situations containing multiple words and referents (Yu & Smith, 2007, Cognition 106: 1558-1568). Cross-situational statistical learning relies on the repeated co-occurrence of words with their intended referents, but simple co-occurrence counts cannot explain the findings. Mutual exclusivity (ME: an assumption of one-to-one mappings) can reduce ambiguity by leveraging prior experience to restrict the number of word-referent pairings considered but can also block learning of non-one-to-one mappings. The present study first trained learners on one-to-one mappings with varying numbers of repetitions. In late training, a new set of word-referent pairs were introduced alongside pretrained pairs; each pretrained pair consistently appeared with a new pair. Results indicate that (1) learners quickly infer new pairs in late training on the basis of their knowledge of pretrained pairs, exhibiting ME; and (2) learners also adaptively relax the ME bias and learn two-to-two mappings involving both pretrained and new words and objects. We present an associative model that accounts for both results using competing familiarity and uncertainty biases.

Correction for dynamic bias error in transmission measurements of void fraction

International Nuclear Information System (INIS)

Andersson, P.; Sundén, E. Andersson; Svärd, S. Jacobsson; Sjöstrand, H.

2012-01-01

Dynamic bias errors occur in transmission measurements, such as X-ray, gamma, or neutron radiography or tomography. This is observed when the properties of the object are not stationary in time and its average properties are assessed. The nonlinear measurement response to changes in transmission within the time scale of the measurement implies a bias, which can be difficult to correct for. A typical example is the tomographic or radiographic mapping of void content in dynamic two-phase flow systems. In this work, the dynamic bias error is described and a method to make a first-order correction is derived. A prerequisite for this method is variance estimates of the system dynamics, which can be obtained using high-speed, time-resolved data acquisition. However, in the absence of such acquisition, a priori knowledge might be used to substitute the time resolved data. Using synthetic data, a void fraction measurement case study has been simulated to demonstrate the performance of the suggested method. The transmission length of the radiation in the object under study and the type of fluctuation of the void fraction have been varied. Significant decreases in the dynamic bias error were achieved to the expense of marginal decreases in precision.

Practical investigation of the gate bias effect on the reverse recovery behavior of the body diode in power MOSFETs

DEFF Research Database (Denmark)

Lindberg-Poulsen, Kristian; Petersen, Lars Press; Ouyang, Ziwei

2014-01-01

This work considers an alternative method of reducing the body diode reverse recovery by taking advantage of the MOSFET body effect, and applying a bias voltage to the gate before reverse recovery. A test method is presented, allowing the accurate measurement of voltage and current waveforms during...... reverse recovery at high di=dt. Different bias voltages and dead times are combined, giving a loss map which makes it possible to evaluate the practical efficacy of gate bias on reducing the MOSFET body diode reverse recovery, while comparing it to the well known methods of dead time optimization...

Galaxy Bias and its Effects on the Baryon Acoustic Oscillations Measurements

International Nuclear Information System (INIS)

Mehta, Kushal T.; Seo, Hee-Jong; Eckel, Jonathan; Eisenstein, Daniel J.; Metchnik, Marc; Pinto, Philip; Xu, Xiaoying

2011-01-01

The baryon acoustic oscillation (BAO) feature in the clustering of matter in the universe serves as a robust standard ruler and hence can be used to map the expansion history of the universe. We use high force resolution simulations to analyze the effects of galaxy bias on the measurements of the BAO signal. We apply a variety of Halo Occupation Distributions (HODs) and produce biased mass tracers to mimic different galaxy populations. We investigate whether galaxy bias changes the non-linear shifts on the acoustic scale relative to the underlying dark matter distribution presented by Seo et al. (2009). For the less biased HOD models (b 3) show a shift at moderate significance (0.79% ± 0.31% for the most extreme case). We test the one-step reconstruction technique introduced by Eisenstein et al. (2007) in the case of realistic galaxy bias and shot noise. The reconstruction scheme increases the correlation between the initial and final (z = 1) density fields achieving an equivalent level of correlation at nearly twice the wavenumber after reconstruction. Reconstruction reduces the shifts and errors on the shifts. We find that after reconstruction the shifts from the galaxy cases and the dark matter case are consistent with each other and with no shift. The 1σ systematic errors on the distance measurements inferred from our BAO measurements with various HODs after reconstruction are about 0.07%-0.15%.

Statistical properties of interval mapping methods on quantitative trait loci location: impact on QTL/eQTL analyses

Directory of Open Access Journals (Sweden)

Wang Xiaoqiang

2012-04-01

Full Text Available Abstract Background Quantitative trait loci (QTL detection on a huge amount of phenotypes, like eQTL detection on transcriptomic data, can be dramatically impaired by the statistical properties of interval mapping methods. One of these major outcomes is the high number of QTL detected at marker locations. The present study aims at identifying and specifying the sources of this bias, in particular in the case of analysis of data issued from outbred populations. Analytical developments were carried out in a backcross situation in order to specify the bias and to propose an algorithm to control it. The outbred population context was studied through simulated data sets in a wide range of situations. The likelihood ratio test was firstly analyzed under the "one QTL" hypothesis in a backcross population. Designs of sib families were then simulated and analyzed using the QTL Map software. On the basis of the theoretical results in backcross, parameters such as the population size, the density of the genetic map, the QTL effect and the true location of the QTL, were taken into account under the "no QTL" and the "one QTL" hypotheses. A combination of two non parametric tests - the Kolmogorov-Smirnov test and the Mann-Whitney-Wilcoxon test - was used in order to identify the parameters that affected the bias and to specify how much they influenced the estimation of QTL location. Results A theoretical expression of the bias of the estimated QTL location was obtained for a backcross type population. We demonstrated a common source of bias under the "no QTL" and the "one QTL" hypotheses and qualified the possible influence of several parameters. Simulation studies confirmed that the bias exists in outbred populations under both the hypotheses of "no QTL" and "one QTL" on a linkage group. The QTL location was systematically closer to marker locations than expected, particularly in the case of low QTL effect, small population size or low density of markers, i

Journal bias or author bias?

Science.gov (United States)

Harris, Ian

2016-01-01

I read with interest the comment by Mark Wilson in the Indian Journal of Medical Ethics regarding bias and conflicts of interest in medical journals. Wilson targets one journal (the New England Journal of Medicine: NEJM) and one particular "scandal" to make his point that journals' decisions on publication are biased by commercial conflicts of interest (CoIs). It is interesting that he chooses the NEJM which, by his own admission, had one of the strictest CoI policies and had published widely on this topic. The feeling is that if the NEJM can be guilty, they can all be guilty.

Significance of Bias Correction in Drought Frequency and Scenario Analysis Based on Climate Models

Science.gov (United States)

Aryal, Y.; Zhu, J.

2015-12-01

Assessment of future drought characteristics is difficult as climate models usually have bias in simulating precipitation frequency and intensity. To overcome this limitation, output from climate models need to be bias corrected based on the specific purpose of applications. In this study, we examine the significance of bias correction in the context of drought frequency and scenario analysis using output from climate models. In particular, we investigate the performance of three widely used bias correction techniques: (1) monthly bias correction (MBC), (2) nested bias correction (NBC), and (3) equidistance quantile mapping (EQM) The effect of bias correction in future scenario of drought frequency is also analyzed. The characteristics of drought are investigated in terms of frequency and severity in nine representative locations in different climatic regions across the United States using regional climate model (RCM) output from the North American Regional Climate Change Assessment Program (NARCCAP). The Standardized Precipitation Index (SPI) is used as the means to compare and forecast drought characteristics at different timescales. Systematic biases in the RCM precipitation output are corrected against the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data. The results demonstrate that bias correction significantly decreases the RCM errors in reproducing drought frequency derived from the NARR data. Preserving mean and standard deviation is essential for climate models in drought frequency analysis. RCM biases both have regional and timescale dependence. Different timescale of input precipitation in the bias corrections show similar results. Drought frequency obtained from the RCM future (2040-2070) scenarios is compared with that from the historical simulations. The changes in drought characteristics occur in all climatic regions. The relative changes in drought frequency in future scenario in relation to

Landslides Mapped from LIDAR Imagery, Kitsap County, Washington

Science.gov (United States)

McKenna, Jonathan P.; Lidke, David J.; Coe, Jeffrey A.

2008-01-01

Landslides are a recurring problem on hillslopes throughout the Puget Lowland, Washington, but can be difficult to identify in the densely forested terrain. However, digital terrain models of the bare-earth surface derived from LIght Detection And Ranging (LIDAR) data express topographic details sufficiently well to identify landslides. Landslides and escarpments were mapped using LIDAR imagery and field checked (when permissible and accessible) throughout Kitsap County. We relied almost entirely on derivatives of LIDAR data for our mapping, including topographic-contour, slope, and hill-shaded relief maps. Each mapped landslide was assigned a level of 'high' or 'moderate' confidence based on the LIDAR characteristics and on field observations. A total of 231 landslides were identified representing 0.8 percent of the land area of Kitsap County. Shallow debris topples along the coastal bluffs and large (>10,000 m2) landslide complexes are the most common types of landslides. The smallest deposit mapped covers an area of 252 m2, while the largest covers 0.5 km2. Previous mapping efforts that relied solely on field and photogrammetric methods identified only 57 percent of the landslides mapped by LIDAR (61 percent high confidence and 39 percent moderate confidence), although nine landslides previously identified were not mapped during this study. The remaining 43 percent identified using LIDAR have 13 percent high confidence and 87 percent moderate confidence. Coastal areas are especially susceptible to landsliding; 67 percent of the landslide area that we mapped lies within 500 meters of the present coastline. The remaining 33 percent are located along drainages farther inland. The LIDAR data we used for mapping have some limitations including (1) rounding of the interface area between low slope surfaces and vertical faces (that is, along the edges of steep escarpments) which results in scarps being mapped too far headward (one or two meters), (2) incorrect laser

Validation of two ribosomal RNA removal methods for microbial metatranscriptomics

Energy Technology Data Exchange (ETDEWEB)

He, Shaomei; Wurtzel, Omri; Singh, Kanwar; Froula, Jeff L; Yilmaz, Suzan; Tringe, Susannah G; Wang, Zhong; Chen, Feng; Lindquist, Erika A; Sorek, Rotem; Hugenholtz, Philip

2010-10-01

The predominance of rRNAs in the transcriptome is a major technical challenge in sequence-based analysis of cDNAs from microbial isolates and communities. Several approaches have been applied to deplete rRNAs from (meta)transcriptomes, but no systematic investigation of potential biases introduced by any of these approaches has been reported. Here we validated the effectiveness and fidelity of the two most commonly used approaches, subtractive hybridization and exonuclease digestion, as well as combinations of these treatments, on two synthetic five-microorganism metatranscriptomes using massively parallel sequencing. We found that the effectiveness of rRNA removal was a function of community composition and RNA integrity for these treatments. Subtractive hybridization alone introduced the least bias in relative transcript abundance, whereas exonuclease and in particular combined treatments greatly compromised mRNA abundance fidelity. Illumina sequencing itself also can compromise quantitative data analysis by introducing a G+C bias between runs.

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

Science.gov (United States)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Correction of Interferometric and Vegetation Biases in the SRTMGL1 Spaceborne DEM with Hydrological Conditioning towards Improved Hydrodynamics Modeling in the Amazon Basin

Directory of Open Access Journals (Sweden)

Sebastien Pinel

2015-12-01

Full Text Available In the Amazon basin, the recently released SRTM Global 1 arc-second (SRTMGL1 remains the best topographic information for hydrological and hydrodynamic modeling purposes. However, its accuracy is hindered by errors, partly due to vegetation, leading to erroneous simulations. Previous efforts to remove the vegetation signal either did not account for its spatial variability or relied on a single assumed percentage of penetration of the SRTM signal. Here, we propose a systematic approach over an Amazonian floodplain to remove the vegetation signal, addressing its heterogeneity by combining estimates of vegetation height and a land cover map. We improve this approach by interpolating the first results with drainage network, field and altimetry data to obtain a hydrological conditioned DEM. The averaged interferometric and vegetation biases over the forest zone were found to be −2.0 m and 7.4 m, respectively. Comparing the original and corrected DEM, vertical validation against Ground Control Points shows a RMSE reduction of 64%. Flood extent accuracy, controlled against Landsat and JERS-1 images, stresses improvements in low and high water periods (+24% and +18%, respectively. This study also highlights that a ground truth drainage network, as a unique input during the interpolation, achieves reasonable results in terms of flood extent and hydrological characteristics.

Reliability improvement for anisotropic biased compensated α/β contamination meter

Energy Technology Data Exchange (ETDEWEB)

Coulon, R., E-mail: romain.coulon@cea.fr [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif-sur-Yvette (France); Montagu, T. [CEA, LIST, Laboratoire de Modélisation et Simulation des Systèmes, F-91191 Gif-sur-Yvette (France); Schoepff, V. [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif-sur-Yvette (France); Menaa, N.; Ulmann, A. Gallozzi; Blanc de Lanaute, N. [CANBERRA France, F-78182 St Quentin en Yvelines (France)

2016-11-21

Nuclear instruments such as alpha/beta contamination meter are frequently used in a compensated mode where the contribution of gamma radiation background is compensated by a guard detector. The signal of interest is then the subtraction of counting from both channels. In practice, the noise signal measured by the guard detector is not strictly equal to the noise contribution into the first detector due to anisotropic biases. The random error (under Poisson assumption) is taken into account to build a hypothesis test. The system is also designed to minimize the systematic error but in some cases, this bias could not be completely removed. The measurement system then shows different behavior when the surrounding environment changes exhibiting inopportune false alarms. A method allowing the false alarms to be suppressed is addressed in this study for compensated measurement. An improvement in terms of reliability has been proven.

Characterizing sampling and quality screening biases in infrared and microwave limb sounding

Science.gov (United States)

Millán, Luis F.; Livesey, Nathaniel J.; Santee, Michelle L.; von Clarmann, Thomas

2018-03-01

This study investigates orbital sampling biases and evaluates the additional impact caused by data quality screening for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Aura Microwave Limb Sounder (MLS). MIPAS acts as a proxy for typical infrared limb emission sounders, while MLS acts as a proxy for microwave limb sounders. These biases were calculated for temperature and several trace gases by interpolating model fields to real sampling patterns and, additionally, screening those locations as directed by their corresponding quality criteria. Both instruments have dense uniform sampling patterns typical of limb emission sounders, producing almost identical sampling biases. However, there is a substantial difference between the number of locations discarded. MIPAS, as a mid-infrared instrument, is very sensitive to clouds, and measurements affected by them are thus rejected from the analysis. For example, in the tropics, the MIPAS yield is strongly affected by clouds, while MLS is mostly unaffected. The results show that upper-tropospheric sampling biases in zonally averaged data, for both instruments, can be up to 10 to 30 %, depending on the species, and up to 3 K for temperature. For MIPAS, the sampling reduction due to quality screening worsens the biases, leading to values as large as 30 to 100 % for the trace gases and expanding the 3 K bias region for temperature. This type of sampling bias is largely induced by the geophysical origins of the screening (e.g. clouds). Further, analysis of long-term time series reveals that these additional quality screening biases may affect the ability to accurately detect upper-tropospheric long-term changes using such data. In contrast, MLS data quality screening removes sufficiently few points that no additional bias is introduced, although its penetration is limited to the upper troposphere, while MIPAS may cover well into the mid-troposphere in cloud-free scenarios. We emphasize that the

Beyond assembly bias: exploring secondary halo biases for cluster-size haloes

Science.gov (United States)

Mao, Yao-Yuan; Zentner, Andrew R.; Wechsler, Risa H.

2018-03-01

Secondary halo bias, commonly known as `assembly bias', is the dependence of halo clustering on a halo property other than mass. This prediction of the Λ Cold Dark Matter cosmology is essential to modelling the galaxy distribution to high precision and interpreting clustering measurements. As the name suggests, different manifestations of secondary halo bias have been thought to originate from halo assembly histories. We show conclusively that this is incorrect for cluster-size haloes. We present an up-to-date summary of secondary halo biases of high-mass haloes due to various halo properties including concentration, spin, several proxies of assembly history, and subhalo properties. While concentration, spin, and the abundance and radial distribution of subhaloes exhibit significant secondary biases, properties that directly quantify halo assembly history do not. In fact, the entire assembly histories of haloes in pairs are nearly identical to those of isolated haloes. In general, a global correlation between two halo properties does not predict whether or not these two properties exhibit similar secondary biases. For example, assembly history and concentration (or subhalo abundance) are correlated for both paired and isolated haloes, but follow slightly different conditional distributions in these two cases. This results in a secondary halo bias due to concentration (or subhalo abundance), despite the lack of assembly bias in the strict sense for cluster-size haloes. Due to this complexity, caution must be exercised in using any one halo property as a proxy to study the secondary bias due to another property.

Distinguishing bias from sensitivity effects in multialternative detection tasks.

Science.gov (United States)

Sridharan, Devarajan; Steinmetz, Nicholas A; Moore, Tirin; Knudsen, Eric I

2014-08-21

Studies investigating the neural bases of cognitive phenomena increasingly employ multialternative detection tasks that seek to measure the ability to detect a target stimulus or changes in some target feature (e.g., orientation or direction of motion) that could occur at one of many locations. In such tasks, it is essential to distinguish the behavioral and neural correlates of enhanced perceptual sensitivity from those of increased bias for a particular location or choice (choice bias). However, making such a distinction is not possible with established approaches. We present a new signal detection model that decouples the behavioral effects of choice bias from those of perceptual sensitivity in multialternative (change) detection tasks. By formulating the perceptual decision in a multidimensional decision space, our model quantifies the respective contributions of bias and sensitivity to multialternative behavioral choices. With a combination of analytical and numerical approaches, we demonstrate an optimal, one-to-one mapping between model parameters and choice probabilities even for tasks involving arbitrarily large numbers of alternatives. We validated the model with published data from two ternary choice experiments: a target-detection experiment and a length-discrimination experiment. The results of this validation provided novel insights into perceptual processes (sensory noise and competitive interactions) that can accurately and parsimoniously account for observers' behavior in each task. The model will find important application in identifying and interpreting the effects of behavioral manipulations (e.g., cueing attention) or neural perturbations (e.g., stimulation or inactivation) in a variety of multialternative tasks of perception, attention, and decision-making. © 2014 ARVO.

Simulating snow maps for Norway: description and statistical evaluation of the seNorge snow model

Directory of Open Access Journals (Sweden)

T. M. Saloranta

2012-11-01

Full Text Available Daily maps of snow conditions have been produced in Norway with the seNorge snow model since 2004. The seNorge snow model operates with 1 × 1 km resolution, uses gridded observations of daily temperature and precipitation as its input forcing, and simulates, among others, snow water equivalent (SWE, snow depth (SD, and the snow bulk density (ρ. In this paper the set of equations contained in the seNorge model code is described and a thorough spatiotemporal statistical evaluation of the model performance from 1957–2011 is made using the two major sets of extensive in situ snow measurements that exist for Norway. The evaluation results show that the seNorge model generally overestimates both SWE and ρ, and that the overestimation of SWE increases with elevation throughout the snow season. However, the R²-values for model fit are 0.60 for (log-transformed SWE and 0.45 for ρ, indicating that after removal of the detected systematic model biases (e.g. by recalibrating the model or expressing snow conditions in relative units the model performs rather well. The seNorge model provides a relatively simple, not very data-demanding, yet nonetheless process-based method to construct snow maps of high spatiotemporal resolution. It is an especially well suited alternative for operational snow mapping in regions with rugged topography and large spatiotemporal variability in snow conditions, as is the case in the mountainous Norway.

Atlas-based analysis of cardiac shape and function: correction of regional shape bias due to imaging protocol for population studies.

Science.gov (United States)

Medrano-Gracia, Pau; Cowan, Brett R; Bluemke, David A; Finn, J Paul; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Suinesiaputra, Avan; Young, Alistair A

2013-09-13

Cardiovascular imaging studies generate a wealth of data which is typically used only for individual study endpoints. By pooling data from multiple sources, quantitative comparisons can be made of regional wall motion abnormalities between different cohorts, enabling reuse of valuable data. Atlas-based analysis provides precise quantification of shape and motion differences between disease groups and normal subjects. However, subtle shape differences may arise due to differences in imaging protocol between studies. A mathematical model describing regional wall motion and shape was used to establish a coordinate system registered to the cardiac anatomy. The atlas was applied to data contributed to the Cardiac Atlas Project from two independent studies which used different imaging protocols: steady state free precession (SSFP) and gradient recalled echo (GRE) cardiovascular magnetic resonance (CMR). Shape bias due to imaging protocol was corrected using an atlas-based transformation which was generated from a set of 46 volunteers who were imaged with both protocols. Shape bias between GRE and SSFP was regionally variable, and was effectively removed using the atlas-based transformation. Global mass and volume bias was also corrected by this method. Regional shape differences between cohorts were more statistically significant after removing regional artifacts due to imaging protocol bias. Bias arising from imaging protocol can be both global and regional in nature, and is effectively corrected using an atlas-based transformation, enabling direct comparison of regional wall motion abnormalities between cohorts acquired in separate studies.

Introducing etch kernels for efficient pattern sampling and etch bias prediction

Science.gov (United States)

Weisbuch, François; Lutich, Andrey; Schatz, Jirka

2018-01-01

Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels, as well as the choice of calibration patterns, is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels-"internal, external, curvature, Gaussian, z_profile"-designed to represent the finest details of the resist geometry to characterize precisely the etch bias at any point along a resist contour. By evaluating the etch kernels on various structures, it is possible to map their etch signatures in a multidimensional space and analyze them to find an optimal sampling of structures. The etch kernels evaluated on these structures were combined with experimental etch bias derived from scanning electron microscope contours to train artificial neural networks to predict etch bias. The method applied to contact and line/space layers shows an improvement in etch model prediction accuracy over standard etch model. This work emphasizes the importance of the etch kernel definition to characterize and predict complex etch effects.

Body Bias usage in UTBB FDSOI designs: A parametric exploration approach

Science.gov (United States)

Puschini, Diego; Rodas, Jorge; Beigne, Edith; Altieri, Mauricio; Lesecq, Suzanne

2016-03-01

Some years ago, UTBB FDSOI has appeared in the horizon of low-power circuit designers. With the 14 nm and 10 nm nodes in the road-map, the industrialized 28 nm platform promises highly efficient designs with Ultra-Wide Voltage Range (UWVR) thanks to extended Body Bias properties. From the power management perspective, this new opportunity is considered as a new degree of freedom in addition to the classic Dynamic Voltage Scaling (DVS), increasing the complexity of the power optimization problem at design time. However, so far no formal or empiric tool allows to early evaluate the real need for a Dynamic Body Bias (DBB) mechanism on future designs. This paper presents a parametric exploration approach that analyzes the benefits of using Body Bias in 28 nm UTBB FDSOI circuits. The exploration is based on electrical simulations of a ring-oscillator structure. These experiences show that a Body Bias strategy is not always required but, they underline the large power reduction that can be achieved when mandatory. Results are summarized in order to help designers to analyze how to choose the best dynamic power management strategy for a given set of operating conditions in terms of temperature, circuit activity and process choice. This exploration contributes to the identification of conditions that make DBB more efficient than DVS, and vice versa, and when both methods are mandatory to optimize power consumption.

CPI Bias in Korea

Directory of Open Access Journals (Sweden)

Chul Chung

2007-12-01

Full Text Available We estimate the CPI bias in Korea by employing the approach of Engel’s Law as suggested by Hamilton (2001. This paper is the first attempt to estimate the bias using Korean panel data, Korean Labor and Income Panel Study(KLIPS. Following Hamilton’s model with non­linear specification correction, our estimation result shows that the cumulative CPI bias over the sample period (2000-2005 was 0.7 percent annually. This CPI bias implies that about 21 percent of the inflation rate during the period can be attributed to the bias. In light of purchasing power parity, we provide an interpretation of the estimated bias.

Producing physically consistent and bias free extreme precipitation events over the Switzerland: Bridging gaps between meteorology and impact models

Science.gov (United States)

José Gómez-Navarro, Juan; Raible, Christoph C.; Blumer, Sandro; Martius, Olivia; Felder, Guido

2016-04-01

Extreme precipitation episodes, although rare, are natural phenomena that can threat human activities, especially in areas densely populated such as Switzerland. Their relevance demands the design of public policies that protect public assets and private property. Therefore, increasing the current understanding of such exceptional situations is required, i.e. the climatic characterisation of their triggering circumstances, severity, frequency, and spatial distribution. Such increased knowledge shall eventually lead us to produce more reliable projections about the behaviour of these events under ongoing climate change. Unfortunately, the study of extreme situations is hampered by the short instrumental record, which precludes a proper characterization of events with return period exceeding few decades. This study proposes a new approach that allows studying storms based on a synthetic, but physically consistent database of weather situations obtained from a long climate simulation. Our starting point is a 500-yr control simulation carried out with the Community Earth System Model (CESM). In a second step, this dataset is dynamically downscaled with the Weather Research and Forecasting model (WRF) to a final resolution of 2 km over the Alpine area. However, downscaling the full CESM simulation at such high resolution is infeasible nowadays. Hence, a number of case studies are previously selected. This selection is carried out examining the precipitation averaged in an area encompassing Switzerland in the ESM. Using a hydrological criterion, precipitation is accumulated in several temporal windows: 1 day, 2 days, 3 days, 5 days and 10 days. The 4 most extreme events in each category and season are selected, leading to a total of 336 days to be simulated. The simulated events are affected by systematic biases that have to be accounted before this data set can be used as input in hydrological models. Thus, quantile mapping is used to remove such biases. For this task

Electrostatic Dust Detection and Removal for ITER

International Nuclear Information System (INIS)

C.H. Skinner; A. Campos; H. Kugel; J. Leisure; A.L. Roquemore; S. Wagner

2008-01-01

We present some recent results on two innovative applications of microelectronics technology to dust inventory measurement and dust removal in ITER. A novel device to detect the settling of dust particles on a remote surface has been developed in the laboratory. A circuit board with a grid of two interlocking conductive traces with 25 (micro)m spacing is biased to 30-50 V. Carbon particles landing on the energized grid create a transient short circuit. The current flowing through the short circuit creates a voltage pulse that is recorded by standard nuclear counting electronics and the total number of counts is related to the mass of dust impinging on the grid. The particles typically vaporize in a few seconds restoring the previous voltage standoff. Experience on NSTX however, showed that in a tokamak environment it was still possible for large particles or fibers to remain on the grid causing a long term short circuit. We report on the development of a gas puff system that uses helium to clear such particles. Experiments with varying nozzle designs, backing pressures, puff durations, and exit flow orientations have given an optimal configuration that effectively removes particles from an area up to 25 cm 2 with a single nozzle. In a separate experiment we are developing an advanced circuit grid of three interlocking traces that can generate a miniature electrostatic traveling wave for transporting dust to a suitable exit port. We have fabricated such a 3-pole circuit board with 25 micron insulated traces that operates with voltages up to 200 V. Recent results showed motion of dust particles with the application of only 50 V bias voltage. Such a device could potentially remove dust continuously without dedicated interventions and without loss of machine availability for plasma operations

Non-iterative relative bias correction for 3D reconstruction of in utero fetal brain MR imaging.

Science.gov (United States)

Kim, Kio; Habas, Piotr; Rajagopalan, Vidya; Scott, Julia; Corbett-Detig, James; Rousseau, Francois; Glenn, Orit; Barkovich, James; Studholme, Colin

2010-01-01

The slice intersection motion correction (SIMC) method is a powerful tool to compensate for motion that occurs during in utero acquisition of the multislice magnetic resonance (MR) images of the human fetal brain. The SIMC method makes use of the slice intersection intensity profiles of orthogonally planned slice pairs to simultaneously correct for the relative motion occurring between all the acquired slices. This approach is based on the assumption that the bias field is consistent between slices. However, for some clinical studies where there is a strong bias field combined with significant fetal motion relative to the coils, this assumption is broken and the resulting motion estimate and the reconstruction to a 3D volume can both contain errors. In this work, we propose a method to correct for the relative differences in bias field between all slice pairs. For this, we define the energy function as the mean square difference of the intersection profiles, that is then minimized with respect to the bias field parameters of the slices. A non iterative method which considers the relative bias between each slice simultaneously is used to efficiently remove inconsistencies. The method, when tested on synthetic simulations and actual clinical imaging studies where bias was an issue, brought a significant improvement to the final reconstructed image.

Demonstration of biased membrane static figure mapping by optical beam subpixel centroid shift

Energy Technology Data Exchange (ETDEWEB)

Pinto, Fabrizio, E-mail: fpinto@jazanu.edu.sa [Laboratory for Quantum Vacuum Applications, Department of Physics, Faculty of Science, Jazan University, P.O. Box 114, Gizan 45142 (Saudi Arabia)

2016-06-10

The measurement of Casimir forces by means of condenser microphones has been shown to be quite promising since its early introduction almost half-a-century ago. However, unlike the remarkable progress achieved in characterizing the vibrating membrane in the dynamical case, the accurate determination of the membrane static figure under electrostatic bias remains a challenge. In this paper, we discuss our first data obtained by measuring the centroid shift of an optical beam with subpixel accuracy by charge coupled device (CCD) and by an extensive analysis of noise sources present in the experimental setup.

Local and sex-specific biases in crossover vs. noncrossover outcomes at meiotic recombination hot spots in mice

Science.gov (United States)

de Boer, Esther; Jasin, Maria; Keeney, Scott

2015-01-01

Meiotic recombination initiated by programmed double-strand breaks (DSBs) yields two types of interhomolog recombination products, crossovers and noncrossovers, but what determines whether a DSB will yield a crossover or noncrossover is not understood. In this study, we analyzed the influence of sex and chromosomal location on mammalian recombination outcomes by constructing fine-scale recombination maps in both males and females at two mouse hot spots located in different regions of the same chromosome. These include the most comprehensive maps of recombination hot spots in oocytes to date. One hot spot, located centrally on chromosome 1, behaved similarly in male and female meiosis: Crossovers and noncrossovers formed at comparable levels and ratios in both sexes. In contrast, at a distal hot spot, crossovers were recovered only in males even though noncrossovers were obtained at similar frequencies in both sexes. These findings reveal an example of extreme sex-specific bias in recombination outcome. We further found that estimates of relative DSB levels are surprisingly poor predictors of relative crossover frequencies between hot spots in males. Our results demonstrate that the outcome of mammalian meiotic recombination can be biased, that this bias can vary depending on location and cellular context, and that DSB frequency is not the only determinant of crossover frequency. PMID:26251527

Can the variability in precipitation simulations across GCMs be reduced through sensible bias correction?

Science.gov (United States)

Nguyen, Ha; Mehrotra, Rajeshwar; Sharma, Ashish

2017-11-01

This work investigates the performance of four bias correction alternatives for representing persistence characteristics of precipitation across 37 General Circulation Models (GCMs) from the CMIP5 data archive. The first three correction approaches are the Simple Monthly Bias Correction (SMBC), Equidistance Quantile Mapping (EQM), and Nested Bias Correction (NBC), all of which operate in the time domain, with a focus on representing distributional and moment attributes in the observed precipitation record. The fourth approach corrects for the biases in high- and low-frequency variability or persistence of the GCM time series in the frequency domain and is named as Frequency-based Bias Correction (FBC). The Climatic Research Unit (CRU) gridded precipitation data covering the global land surface is used as a reference dataset. The assessment focusses on current and future means, variability, and drought-related characteristics at different temporal and spatial scales. For the current climate, all bias correction approaches perform reasonably well at the global scale by reproducing the observed precipitation statistics. For the future climate, focus is drawn on the agreement of the attributes across the GCMs considered. The inter-model difference/spread of each attribute across the GCMs is used as a measure of this agreement. Our results indicate that out of the four bias correction approaches used, FBC provides the lowest inter-model spreads, specifically for persistence attributes, over most regions/ parts over the global land surface. This has significant implications for most hydrological studies where the effect of low-frequency variability is of considerable importance.

Exchange bias and bistable magneto-resistance states in amorphous TbFeCo thin films

Energy Technology Data Exchange (ETDEWEB)

Li, Xiaopu, E-mail: xl6ba@virginia.edu; Ma, Chung T.; Poon, S. Joseph, E-mail: sjp9x@virginia.edu [Department of Physics, University of Virginia, Charlottesville, Virginia 22904 (United States); Lu, Jiwei [Department of Materials Science and Engineering, University of Virginia, Charlottesville, Virginia 22904 (United States); Devaraj, Arun [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States); Spurgeon, Steven R.; Comes, Ryan B. [Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States)

2016-01-04

Amorphous TbFeCo thin films sputter deposited at room temperature on thermally oxidized Si substrate are found to exhibit strong perpendicular magnetic anisotropy. Atom probe tomography, scanning transmission electron microscopy, and energy dispersive X-ray spectroscopy mapping have revealed two nanoscale amorphous phases with different Tb atomic percentages distributed within the amorphous film. Exchange bias accompanied by bistable magneto-resistance states has been uncovered near room temperature by magnetization and magneto-transport measurements. The exchange anisotropy originates from the exchange interaction between the ferrimagnetic and ferromagnetic components corresponding to the two amorphous phases. This study provides a platform for exchange bias and magneto-resistance switching using single-layer amorphous ferrimagnetic thin films that require no epitaxial growth.

Approximate Bias Correction in Econometrics

OpenAIRE

James G. MacKinnon; Anthony A. Smith Jr.

1995-01-01

This paper discusses ways to reduce the bias of consistent estimators that are biased in finite samples. It is necessary that the bias function, which relates parameter values to bias, should be estimable by computer simulation or by some other method. If so, bias can be reduced or, in some cases that may not be unrealistic, even eliminated. In general, several evaluations of the bias function will be required to do this. Unfortunately, reducing bias may increase the variance, or even the mea...

Investigation of heavy metal removal from motorway stormwater using inorganic ion exchange

International Nuclear Information System (INIS)

Pitcher, Sarah

2002-01-01

Stormwater runoff from motorway surfaces contains toxic heavy metals that are not sufficiently removed by current treatment systems. This research has investigated the potential use of inorganic ion exchange materials to further reduce the levels of dissolved heavy metals. Candidate materials (synthetic/natural zeolites, clay/modified clay, hydrotalcite, lignite) were tested by a shaking procedure (mixed 5 mg dm -3 of each heavy metals, shaken for 10 min) and analysed by atomic absorption spectrometry. The synthetic zeolites MAP and Y showed 100% heavy metal removal and were investigated further by a series of batch experiments. The zeolites exhibited a selectivity sequence Pb > Cu > Cd ∼ Zn. Zeolite MAP has a high capacity for heavy metal uptake (4.5 meq g -1 ), but is not practical for use in a treatment facility owing to its low particle size (3 μm). However, large zeolite pellets (∼ 2 mm) were found to have a low heavy metal uptake (∼ 44 %) due to diffusion limitations. Selected materials (zeolites MAP, Y, mordenite, and carbon-based lignite) were tested in actual and spiked motorway stormwater. The synthetic zeolites effectively remove heavy metals (∼ 100 %) but change the environmental chemistry of the stormwater by releasing high concentrations of sodium, removing calcium ions and increasing the solution pH. The presence of other dissolved contaminants in motorway stormwater inhibited the uptake of heavy metals by the natural zeolite mordenite (34 % less removal). Alkali/alkaline-earth metals (Na, Ca) in solution compete for exchange sites in lignite and mordenite, reducing the heavy metal uptake. Chloride in solution forms complexes with cadmium, severely reducing its uptake by zeolite Y. The presence of dissolved road salt is a potentially serious concern as it causes previously exchanged heavy metals to be re-eluted, especially zinc and cadmium. Zeolite MAP as an exchanger is relatively unaffected by road salt. There is potential for the use of

Measurement of the $B^-$ lifetime using a simulation free approach for trigger bias correction

Energy Technology Data Exchange (ETDEWEB)

Aaltonen, T.; /Helsinki Inst. of Phys.; Adelman, J.; /Chicago U., EFI; Alvarez Gonzalez, B.; /Cantabria Inst. of Phys.; Amerio, S.; /INFN, Padua; Amidei, D.; /Michigan U.; Anastassov, A.; /Northwestern U.; Annovi, A.; /Frascati; Antos, J.; /Comenius U.; Apollinari, G.; /Fermilab; Appel, J.; /Fermilab; Apresyan, A.; /Purdue U. /Waseda U.

2010-04-01

The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. In this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B{sup -} using the mode B{sup -} {yields} D{sup 0}{pi}{sup -}. The B{sup -} lifetime is measured as {tau}{sub B{sup -}} = 1.663 {+-} 0.023 {+-} 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.

Measurement of the B- lifetime using a simulation free approach for trigger bias correction

International Nuclear Information System (INIS)

2010-01-01

The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. In this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B - using the mode B - → D 0 π - . The B - lifetime is measured as τ B# sup -# = 1.663 ± 0.023 ± 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.

Bias caused by water adsorption in hourly PM measurements

Science.gov (United States)

Kiss, Gyula; Imre, Kornélia; Molnár, Ágnes; Gelencsér, András

2017-07-01

Beta-attenuation monitors are used worldwide to monitor PM mass concentration with high temporal resolution. Hourly PM10 and PM2. 5 dry mass concentrations are publicly available with the tacit assumption that water is effectively removed prior to the measurement. However, as both the filter material of the monitor and the aerosol particles are capable of retaining a significant amount of water even at low relative humidities, the basic assumption may not be valid, resulting in significant bias in reported PM10 and PM2. 5 concentrations. Here we show that in PM10 measurement, particle-free air can produce apparent hourly average PM concentrations in the range of -13-+21 µg m-3 under conditions of fluctuating relative humidity. Positive and negative apparent readings are observed with increasing and decreasing relative humidities, respectively. Similar phenomena have been observed when the instrument filter was previously loaded with atmospheric aerosol. As a result the potential measurement biases in hourly readings arising from the interaction with water may be in the range of -53… + 69 %.

The National Map - Orthoimagery

Science.gov (United States)

Mauck, James; Brown, Kim; Carswell, William J.

2009-01-01

Orthorectified digital aerial photographs and satellite images of 1-meter (m) pixel resolution or finer make up the orthoimagery component of The National Map. The process of orthorectification removes feature displacements and scale variations caused by terrain relief and sensor geometry. The result is a combination of the image characteristics of an aerial photograph or satellite image and the geometric qualities of a map. These attributes allow users to: *Measure distance *Calculate areas *Determine shapes of features *Calculate directions *Determine accurate coordinates *Determine land cover and use *Perform change detection *Update maps The standard digital orthoimage is a 1-m or finer resolution, natural color or color infra-red product. Most are now produced as GeoTIFFs and accompanied by a Federal Geographic Data Committee (FGDC)-compliant metadata file. The primary source for 1-m data is the National Agriculture Imagery Program (NAIP) leaf-on imagery. The U.S. Geological Survey (USGS) utilizes NAIP imagery as the image layer on its 'Digital- Map' - a new generation of USGS topographic maps (http://nationalmap.gov/digital_map). However, many Federal, State, and local governments and organizations require finer resolutions to meet a myriad of needs. Most of these images are leaf-off, natural-color products at resolutions of 1-foot (ft) or finer.

Correction of Selection Bias in Survey Data: Is the Statistical Cure Worse Than the Bias?

Science.gov (United States)

Hanley, James A

2017-04-01

In previous articles in the American Journal of Epidemiology (Am J Epidemiol. 2013;177(5):431-442) and American Journal of Public Health (Am J Public Health. 2013;103(10):1895-1901), Masters et al. reported age-specific hazard ratios for the contrasts in mortality rates between obesity categories. They corrected the observed hazard ratios for selection bias caused by what they postulated was the nonrepresentativeness of the participants in the National Health Interview Study that increased with age, obesity, and ill health. However, it is possible that their regression approach to remove the alleged bias has not produced, and in general cannot produce, sensible hazard ratio estimates. First, we must consider how many nonparticipants there might have been in each category of obesity and of age at entry and how much higher the mortality rates would have to be in nonparticipants than in participants in these same categories. What plausible set of numerical values would convert the ("biased") decreasing-with-age hazard ratios seen in the data into the ("unbiased") increasing-with-age ratios that they computed? Can these values be encapsulated in (and can sensible values be recovered from) one additional internal variable in a regression model? Second, one must examine the age pattern of the hazard ratios that have been adjusted for selection. Without the correction, the hazard ratios are attenuated with increasing age. With it, the hazard ratios at older ages are considerably higher, but those at younger ages are well below one. Third, one must test whether the regression approach suggested by Masters et al. would correct the nonrepresentativeness that increased with age and ill health that I introduced into real and hypothetical data sets. I found that the approach did not recover the hazard ratio patterns present in the unselected data sets: the corrections overshot the target at older ages and undershot it at lower ages.

Reducing biases on H0 measurements using strong lensing and galaxy dynamics: results from the EAGLE simulation

Science.gov (United States)

Tagore, Amitpal S.; Barnes, David J.; Jackson, Neal; Kay, Scott T.; Schaller, Matthieu; Schaye, Joop; Theuns, Tom

2018-03-01

Cosmological parameter constraints from observations of time-delay lenses are becoming increasingly precise. However, there may be significant bias and scatter in these measurements due to, among other things, the so-called mass-sheet degeneracy. To estimate these uncertainties, we analyse strong lenses from the largest EAGLE hydrodynamical simulation. We apply a mass-sheet transformation to the radial density profiles of lenses, and by selecting lenses near isothermality, we find that the bias on H0 can be reduced to 5 per cent with an intrinsic scatter of 10 per cent, confirming previous results performed on a different simulation data set. We further investigate whether combining lensing observables with kinematic constraints helps to minimize this bias. We do not detect any significant dependence of the bias on lens model parameters or observational properties of the galaxy, but depending on the source-lens configuration, a bias may still exist. Cross lenses provide an accurate estimate of the Hubble constant, while fold (double) lenses tend to be biased low (high). With kinematic constraints, double lenses show bias and intrinsic scatter of 6 per cent and 10 per cent, respectively, while quad lenses show bias and intrinsic scatter of 0.5 per cent and 10 per cent, respectively. For lenses with a reduced χ2 > 1, a power-law dependence of the χ2 on the lens environment (number of nearby galaxies) is seen. Lastly, we model, in greater detail, the cases of two double lenses that are significantly biased. We are able to remove the bias, suggesting that the remaining biases could also be reduced by carefully taking into account additional sources of systematic uncertainty.

Beyond attentional bias: a perceptual bias in a dot-probe task.

Science.gov (United States)

Bocanegra, Bruno R; Huijding, Jorg; Zeelenberg, René

2012-12-01

Previous dot-probe studies indicate that threat-related face cues induce a bias in spatial attention. Independently of spatial attention, a recent psychophysical study suggests that a bilateral fearful face cue improves low spatial-frequency perception (LSF) and impairs high spatial-frequency perception (HSF). Here, we combine these separate lines of research within a single dot-probe paradigm. We found that a bilateral fearful face cue, compared with a bilateral neutral face cue, speeded up responses to LSF targets and slowed down responses to HSF targets. This finding is important, as it shows that emotional cues in dot-probe tasks not only bias where information is preferentially processed (i.e., an attentional bias in spatial location), but also bias what type of information is preferentially processed (i.e., a perceptual bias in spatial frequency). PsycINFO Database Record (c) 2012 APA, all rights reserved.

Simulating publication bias

DEFF Research Database (Denmark)

Paldam, Martin

is censoring: selection by the size of estimate; SR3 selects the optimal combination of fit and size; and SR4 selects the first satisficing result. The last four SRs are steered by priors and result in bias. The MST and the FAT-PET have been developed for detection and correction of such bias. The simulations......Economic research typically runs J regressions for each selected for publication – it is often selected as the ‘best’ of the regressions. The paper examines five possible meanings of the word ‘best’: SR0 is ideal selection with no bias; SR1 is polishing: selection by statistical fit; SR2...... are made by data variation, while the model is the same. It appears that SR0 generates narrow funnels much at odds with observed funnels, while the other four funnels look more realistic. SR1 to SR4 give the mean a substantial bias that confirms the prior causing the bias. The FAT-PET MRA works well...

A study on investors’ personality characteristics and behavioral biases: Conservatism bias and availability bias in the Tehran Stock Exchange

Directory of Open Access Journals (Sweden)

Mahmoud Moradi

2013-04-01

Full Text Available Most economic and finance theories are based on the assumption that during economic decision making, people would act totally rational and consider all available information. Nevertheless, behavioral finance focuses on studying of the role of psychological factors on economic participants’ behavior. The study shows that in real-world environment, people are influenced by emotional and cognitive errors and may make irrational financial decisions. In many cases, the participants of financial markets are not aware of their talents for error in decision making, so they are dissatisfied with their investments by considering some behavioral biases decisions. These decisions may often yield undesirable outcomes, which could influence economy, significantly. This paper presents a survey on the relationship between personality dimensions with behavioral biases and availability bias among investment managers in the Tehran Stock Exchange using SPSS software, descriptive and inferential statistics. The necessary data are collected through questionnaire and they are analyzed using some statistical tests. The preliminary results indicate that there is a relationship between personality dimensions and behavioral biases like conservatism bias and availability bias among the investors in the Tehran Stock Exchange.

Model Consistent Pseudo-Observations of Precipitation and Their Use for Bias Correcting Regional Climate Models

Directory of Open Access Journals (Sweden)

Peter Berg

2015-01-01

Full Text Available Lack of suitable observational data makes bias correction of high space and time resolution regional climate models (RCM problematic. We present a method to construct pseudo-observational precipitation data bymerging a large scale constrained RCMreanalysis downscaling simulation with coarse time and space resolution observations. The large scale constraint synchronizes the inner domain solution to the driving reanalysis model, such that the simulated weather is similar to observations on a monthly time scale. Monthly biases for each single month are corrected to the corresponding month of the observational data, and applied to the finer temporal resolution of the RCM. A low-pass filter is applied to the correction factors to retain the small spatial scale information of the RCM. The method is applied to a 12.5 km RCM simulation and proven successful in producing a reliable pseudo-observational data set. Furthermore, the constructed data set is applied as reference in a quantile mapping bias correction, and is proven skillful in retaining small scale information of the RCM, while still correcting the large scale spatial bias. The proposed method allows bias correction of high resolution model simulations without changing the fine scale spatial features, i.e., retaining the very information required by many impact models.

Optimalisation of magnesium ammonium phosphate precipitation and its applicability to the removal of ammonium.

Science.gov (United States)

Demeestere, K; Smet, E; Van Langenhove, H; Galbacs, Z

2001-12-01

Among the physico-chemical abatement technologies, mainly acid scrubbers have been used to control NH3-emission. The disadvantage of this technique is that it yields waste water, highly concentrated in ammonia. In this report, the applicability of the magnesium ammonium phosphate (MAP) process to regenerate the liquid phase, produced by scrubbing NH3-loaded waste gases, was investigated. In the MAP process, ammonium is precipitated as magnesium ammonium phosphate, which can be used as a slow release fertilizer. The influence of a number of parameters, e.g. pH, kinetics, molar ratio NH(+)4/Mg2+/PO(3-)4 on the efficiency of the formation of MAP and on the ammonium removal efficiency was investigated. In this way, optimal conditions were determined for the precipitation reaction. Next to this, interference caused by other precipitation reactions was studied. At aqueous NH(+)4-concentrations of about 600 mg l(-1), ammonium removal efficiencies of 97% could be obtained at a molar ratio NH(+)4/Mg2+/PO(3-)4 of 1/1.5/1.5. To obtain this result, the pH was continuously adjusted to a value of 9 during the reaction. According to this study, it is obvious that the MAP-precipitation technology offers opportunities for ammonium removal from scrubbing liquids. The practical applicability of the MAP-process in waste gas treatment systems, however, should be the subject for further investigations.

Estimating Gravity Biases with Wavelets in Support of a 1-cm Accurate Geoid Model

Science.gov (United States)

Ahlgren, K.; Li, X.

2017-12-01

Systematic errors that reside in surface gravity datasets are one of the major hurdles in constructing a high-accuracy geoid model at high resolutions. The National Oceanic and Atmospheric Administration's (NOAA) National Geodetic Survey (NGS) has an extensive historical surface gravity dataset consisting of approximately 10 million gravity points that are known to have systematic biases at the mGal level (Saleh et al. 2013). As most relevant metadata is absent, estimating and removing these errors to be consistent with a global geopotential model and airborne data in the corresponding wavelength is quite a difficult endeavor. However, this is crucial to support a 1-cm accurate geoid model for the United States. With recently available independent gravity information from GRACE/GOCE and airborne gravity from the NGS Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project, several different methods of bias estimation are investigated which utilize radial basis functions and wavelet decomposition. We estimate a surface gravity value by incorporating a satellite gravity model, airborne gravity data, and forward-modeled topography at wavelet levels according to each dataset's spatial wavelength. Considering the estimated gravity values over an entire gravity survey, an estimate of the bias and/or correction for the entire survey can be found and applied. In order to assess the accuracy of each bias estimation method, two techniques are used. First, each bias estimation method is used to predict the bias for two high-quality (unbiased and high accuracy) geoid slope validation surveys (GSVS) (Smith et al. 2013 & Wang et al. 2017). Since these surveys are unbiased, the various bias estimation methods should reflect that and provide an absolute accuracy metric for each of the bias estimation methods. Secondly, the corrected gravity datasets from each of the bias estimation methods are used to build a geoid model. The accuracy of each geoid model

Undesirable Choice Biases with Small Differences in the Spatial Structure of Chance Stimulus Sequences.

Directory of Open Access Journals (Sweden)

David Herrera

Full Text Available In two-alternative discrimination tasks, experimenters usually randomize the location of the rewarded stimulus so that systematic behavior with respect to irrelevant stimuli can only produce chance performance on the learning curves. One way to achieve this is to use random numbers derived from a discrete binomial distribution to create a 'full random training schedule' (FRS. When using FRS, however, sporadic but long laterally-biased training sequences occur by chance and such 'input biases' are thought to promote the generation of laterally-biased choices (i.e., 'output biases'. As an alternative, a 'Gellerman-like training schedule' (GLS can be used. It removes most input biases by prohibiting the reward from appearing on the same location for more than three consecutive trials. The sequence of past rewards obtained from choosing a particular discriminative stimulus influences the probability of choosing that same stimulus on subsequent trials. Assuming that the long-term average ratio of choices matches the long-term average ratio of reinforcers, we hypothesized that a reduced amount of input biases in GLS compared to FRS should lead to a reduced production of output biases. We compared the choice patterns produced by a 'Rational Decision Maker' (RDM in response to computer-generated FRS and GLS training sequences. To create a virtual RDM, we implemented an algorithm that generated choices based on past rewards. Our simulations revealed that, although the GLS presented fewer input biases than the FRS, the virtual RDM produced more output biases with GLS than with FRS under a variety of test conditions. Our results reveal that the statistical and temporal properties of training sequences interacted with the RDM to influence the production of output biases. Thus, discrete changes in the training paradigms did not translate linearly into modifications in the pattern of choices generated by a RDM. Virtual RDMs could be further employed to guide

Undesirable Choice Biases with Small Differences in the Spatial Structure of Chance Stimulus Sequences.

Science.gov (United States)

Herrera, David; Treviño, Mario

2015-01-01

In two-alternative discrimination tasks, experimenters usually randomize the location of the rewarded stimulus so that systematic behavior with respect to irrelevant stimuli can only produce chance performance on the learning curves. One way to achieve this is to use random numbers derived from a discrete binomial distribution to create a 'full random training schedule' (FRS). When using FRS, however, sporadic but long laterally-biased training sequences occur by chance and such 'input biases' are thought to promote the generation of laterally-biased choices (i.e., 'output biases'). As an alternative, a 'Gellerman-like training schedule' (GLS) can be used. It removes most input biases by prohibiting the reward from appearing on the same location for more than three consecutive trials. The sequence of past rewards obtained from choosing a particular discriminative stimulus influences the probability of choosing that same stimulus on subsequent trials. Assuming that the long-term average ratio of choices matches the long-term average ratio of reinforcers, we hypothesized that a reduced amount of input biases in GLS compared to FRS should lead to a reduced production of output biases. We compared the choice patterns produced by a 'Rational Decision Maker' (RDM) in response to computer-generated FRS and GLS training sequences. To create a virtual RDM, we implemented an algorithm that generated choices based on past rewards. Our simulations revealed that, although the GLS presented fewer input biases than the FRS, the virtual RDM produced more output biases with GLS than with FRS under a variety of test conditions. Our results reveal that the statistical and temporal properties of training sequences interacted with the RDM to influence the production of output biases. Thus, discrete changes in the training paradigms did not translate linearly into modifications in the pattern of choices generated by a RDM. Virtual RDMs could be further employed to guide the selection of

EFFECTS OF BIASES IN VIRIAL MASS ESTIMATION ON COSMIC SYNCHRONIZATION OF QUASAR ACCRETION

International Nuclear Information System (INIS)

Steinhardt, Charles L.

2011-01-01

Recent work using virial mass estimates and the quasar mass-luminosity plane has yielded several new puzzles regarding quasar accretion, including a sub-Eddington boundary (SEB) on most quasar accretion, near-independence of the accretion rate from properties of the host galaxy, and a cosmic synchronization of accretion among black holes of a common mass. We consider how these puzzles might change if virial mass estimation turns out to have a systematic bias. As examples, we consider two recent claims of mass-dependent biases in Mg II masses. Under any such correction, the surprising cosmic synchronization of quasar accretion rates and independence from the host galaxy remain. The slope and location of the SEB are very sensitive to biases in virial mass estimation, and various mass calibrations appear to favor different possible physical explanations for feedback between the central black hole and its environment. The alternative mass estimators considered do not simply remove puzzling quasar behavior, but rather replace it with new puzzles that may be more difficult to solve than those using current virial mass estimators and the Shen et al. catalog.

Hybrid biasing approaches for global variance reduction

International Nuclear Information System (INIS)

Wu, Zeyun; Abdel-Khalik, Hany S.

2013-01-01

A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.

Media bias under direct and indirect government control: when is the bias smaller?

OpenAIRE

Abhra Roy

2015-01-01

We present an analytical framework to compare media bias under direct and indirect government control. In this context, we show that direct control can lead to a smaller bias and higher welfare than indirect control. We further show that the size of the advertising market affects media bias only under direct control. Media bias, under indirect control, is not affected by the size of the advertising market.

Large-scale galaxy bias

Science.gov (United States)

Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian

2018-02-01

This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Toward behavioural innovation economics – Heuristics and biases in choice under novelty

OpenAIRE

Kate Morrison; Jason Potts

2008-01-01

A framework for ‘behavioural innovation economics’ is proposed here as a synthesis of behavioural economics and innovation economics in the specific context of choice under novelty. We seek to apply the heuristics and biases framework of behavioural economics to the study of the innovation process in order to map and analyze systematic choice failures in the innovation process. We elaborate the distinction between choice under uncertainty and choice under novelty, as well as drawing out the ‘...

Carrier and aberrations removal in interferometric fringe projection profilometry

Science.gov (United States)

Blain, P.; Michel, F.; Renotte, Y.; Habraken, S.

2012-04-01

A profilometer which takes advantage of polarization states splitting technique and monochromatic light projection method as a way to overcome ambient lighting for in-situ measurement is under development [1, 2]. Because of the Savart plate which refracts two out of axis beams, the device suffers from aberrations (mostly coma and astigmatism). These aberrations affect the quality of the sinusoidal fringe pattern. In fringe projection profilometry, the unwrapped phase distribution map contains the sum of the object's shape-related phase and carrier-fringe-related phase. In order to extract the 3D shape of the object, the carrier phase has to be removed [3, 4]. An easy way to remove both the fringe carrier and the aberrations of the optical system is to measure the phases of the test object and to measure the phase of a reference plane with the same set up and to subtract both phase maps. This time consuming technique is suitable for laboratory but not for industry. We propose a method to numerically remove both the fringe carrier and the aberrations. A first reference phase of a calibration plane is evaluated knowing the position of the different elements in the set up and the orientation of the fringes. Then a fitting of the phase map by Zernike polynomials is computed [5]. As the triangulation parameters are known during the calibration, the computation of Zernike coefficients has only to be made once. The wavefront error can be adjusted by a scale factor which depends on the position of the test object.

Variable day/night bias in 24-h non-invasive finger pressure against intrabrachial artery pressure is removed by waveform filtering and level correction

NARCIS (Netherlands)

Westerhof, Berend E.; Guelen, Ilja; Parati, Gianfranco; Groppelli, Antonella; van Montfrans, Gert A.; Wieling, Wouter; Wesseling, Karel H.; Bos, Willem Jan W.

2002-01-01

Background Twenty-four-hour finger arterial pressure (FAP) recordings show a negative bias against intrabrachial artery pressure (BAP) and the bias is greater during the night thereby overestimating the nocturnal blood pressure dip. We have available a methodology with which to reconstruct BAP from

Chiral Biases in Solids by Effect of Shear Gradients: A Speculation on the Deterministic Origin of Biological Homochirality

International Nuclear Information System (INIS)

Arteaga, O.; Canillas, A.; Crusats, Joaquim; Hachemi, Zoubir; Jellison, Gerald Earle Jr.; Llorca, Jordi; Ribo, Josep M.

2010-01-01

We present an experimental approach to the study of the chirality of three CM2 meteorite solid samples by direct measurement of the optical activity (circular birefringence; CB). The measurements are based on transmission two modulator generalized ellipsometry in conjuction with microscope optics to map the CB of the samples. In spite of the complexity of such optical analysis, these first results indicate the presence of optically active areas in the meteorite solid matrix. In the case of the Murchison sample the statistics of the CB mapping shows a bimodal distribution with a bias to negative CB values. The composition of the active areas probably corresponds to serpentines and other poorly identified phyllosilicate phases. The results are compatible with the hypothesis that in a mineral-based scenario for the origin of life a CB sign bias in the chiral fractures originated by mechanical and flow shear gradients on clays could be later transferred to the reactions of the absorbed organic compounds.

Thermoacoustic and thermoreflectance imaging of biased integrated circuits: Voltage and temperature maps

Energy Technology Data Exchange (ETDEWEB)

Hernández-Rosales, E.; Cedeño, E. [Gleb Wataghin Physics Institute, University of Campinas - Unicamp, 13083-859 Campinas, SP (Brazil); Instituto Politécnico Nacional, Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Legaria 694, Colonia Irrigación, CP 11500, México, DF (Mexico); Hernandez-Wong, J. [Instituto Politécnico Nacional, Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Legaria 694, Colonia Irrigación, CP 11500, México, DF (Mexico); CONACYT, México, DF, México (Mexico); Rojas-Trigos, J. B.; Marin, E. [Instituto Politécnico Nacional, Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Legaria 694, Colonia Irrigación, CP 11500, México, DF (Mexico); Gandra, F. C. G.; Mansanares, A. M., E-mail: manoel@ifi.unicamp.br [Gleb Wataghin Physics Institute, University of Campinas - Unicamp, 13083-859 Campinas, SP (Brazil)

2016-07-25

In this work a combined thermoacoustic and thermoreflectance set-up was designed for imaging biased microelectronic circuits. In particular, it was used with polycrystalline silicon resistive tracks grown on a monocrystalline Si substrate mounted on a test chip. Thermoreflectance images, obtained by scanning a probe laser beam on the sample surface, clearly show the regions periodically heated by Joule effect, which are associated to the electric current distribution in the circuit. The thermoacoustic signal, detected by a pyroelectric/piezoelectric sensor beneath the chip, also discloses the Joule contribution of the whole sample. However, additional information emerges when a non-modulated laser beam is focused on the sample surface in a raster scan mode allowing imaging of the sample. The distribution of this supplementary signal is related to the voltage distribution along the circuit.

Quantitative multi-parameter mapping of R1, PD*, MT and R2* at 3T: a multi-center validation

Directory of Open Access Journals (Sweden)

Nikolaus eWeiskopf

2013-06-01

Full Text Available Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1mm high-resolution maps of the longitudinal relaxation rate (R1=1/T1, effective proton density (PD*, magnetization transfer saturation (MT and effective transverse relaxation rate (R2*=1/T2*. MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV for typical morphometric measures (i.e., gray matter probability maps used in voxel-based morphometry and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1% and 8%, respectively, except for the inter-site CoV of R2* (< 20%. The gray matter probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived gray matter probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Large-scale galaxy bias

Science.gov (United States)

Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian

2018-01-01

Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Information environment, behavioral biases, and home bias in analysts’ recommendations

DEFF Research Database (Denmark)

Farooq, Omar; Taouss, Mohammed

2012-01-01

Can information environment of a firm explain home bias in analysts’ recommendations? Can the extent of agency problems explain optimism difference between foreign and local analysts? This paper answers these questions by documenting the effect of information environment on home bias in analysts’...

Examining sources of bias in radiocarbon ages of New Zealand Kiore

Energy Technology Data Exchange (ETDEWEB)

Beavan, N.R.; Sparks, R.J. [Institute of Geological and Nuclear Sciences, (New Zealand). Rafter Radiocarbon Laboratory

1997-12-31

Recent AMS dates for the Pacific rat (Rattus exulans / Kiore) from natural and archaeological sites are significantly older than the generally accepted time for human arrival in New Zealand. Because Rattus exulans is recognized as a human commensal for Polynesian colonization in Oceania, radiocarbon ages for Kiore could be used as an indicator of earliest human contact with New Zealand. A strictly chronological interpretation of the radiocarbon ages assembled, though, raises serious questions about this arrival time. Therefore, factors that could affect the age determinations were also examined. A research programme in progress at the Rafter Radiocarbon Laboratory aims to identify the range and influence of natural bias and variance in radiocarbon ages in kiore bone samples. It was found that the main factors that could bias these ages were the incomplete removal of contaminants by the current bone preparation methods, and dietary carbon reservoir effects. Preliminary results of the various analytical techniques employed are presented.

A Hybrid Framework to Bias Correct and Empirically Downscale Daily Temperature and Precipitation from Regional Climate Models

Science.gov (United States)

Tan, P.; Abraham, Z.; Winkler, J. A.; Perdinan, P.; Zhong, S. S.; Liszewska, M.

2013-12-01

Bias correction and statistical downscaling are widely used approaches for postprocessing climate simulations generated by global and/or regional climate models. The skills of these approaches are typically assessed in terms of their ability to reproduce historical climate conditions as well as the plausibility and consistency of the derived statistical indicators needed by end users. Current bias correction and downscaling approaches often do not adequately satisfy the two criteria of accurate prediction and unbiased estimation. To overcome this limitation, a hybrid regression framework was developed to both minimize prediction errors and preserve the distributional characteristics of climate observations. Specifically, the framework couples the loss functions of standard (linear or nonlinear) regression methods with a regularization term that penalizes for discrepancies between the predicted and observed distributions. The proposed framework can also be extended to generate physically-consistent outputs across multiple response variables, and to incorporate both reanalysis-driven and GCM-driven RCM outputs into a unified learning framework. The effectiveness of the framework is demonstrated using daily temperature and precipitation simulations from the North American Regional Climate Change Program (NARCCAP) . The accuracy of the framework is comparable to standard regression methods, but, unlike the standard regression methods, the proposed framework is able to preserve many of the distribution properties of the response variables, akin to bias correction approaches such as quantile mapping and bivariate geometric quantile mapping.

Estimation bias from using nonlinear Fourier plane correlators for sub-pixel image shift measurement and implications for the binary joint transform correlator

Science.gov (United States)

Grycewicz, Thomas J.; Florio, Christopher J.; Franz, Geoffrey A.; Robinson, Ross E.

2007-09-01

When using Fourier plane digital algorithms or an optical correlator to measure the correlation between digital images, interpolation by center-of-mass or quadratic estimation techniques can be used to estimate image displacement to the sub-pixel level. However, this can lead to a bias in the correlation measurement. This bias shifts the sub-pixel output measurement to be closer to the nearest pixel center than the actual location. The paper investigates the bias in the outputs of both digital and optical correlators, and proposes methods to minimize this effect. We use digital studies and optical implementations of the joint transform correlator to demonstrate optical registration with accuracies better than 0.1 pixels. We use both simulations of image shift and movies of a moving target as inputs. We demonstrate bias error for both center-of-mass and quadratic interpolation, and discuss the reasons that this bias is present. Finally, we suggest measures to reduce or eliminate the bias effects. We show that when sub-pixel bias is present, it can be eliminated by modifying the interpolation method. By removing the bias error, we improve registration accuracy by thirty percent.

Multitracer CMB delensing maps from Planck and WISE data

Science.gov (United States)

Yu, Byeonghee; Hill, J. Colin; Sherwin, Blake D.

2017-12-01

Delensing, the removal of the limiting lensing B -mode background, is crucial for the success of future cosmic microwave background (CMB) surveys in constraining inflationary gravitational waves (IGWs). In recent work, delensing with large-scale structure tracers has emerged as a promising method both for improving constraints on IGWs and for testing delensing methods for future use. However, the delensing fractions (i.e., the fraction of the lensing-B mode power removed) achieved by recent efforts have been only 20%-30%. In this work, we provide a detailed characterization of a full-sky, dust-cleaned cosmic infrared background (CIB) map for delensing and construct a further-improved delensing template by adding additional tracers to increase delensing performance. In particular, we build a multitracer delensing template by combining the dust-cleaned Planck CIB map with a reconstructed CMB lensing map from Planck and a galaxy number density map from the Wide-field Infrared Survey Explorer (WISE) satellite. For this combination, we calculate the relevant weightings by fitting smooth templates to measurements of all the cross-spectra and autospectra of these maps. On a large fraction of the sky (fsky=0.43 ), we demonstrate that our maps are capable of providing a delensing factor of 43 ±1 % ; using a more restrictive mask (fsky=0.11 ), the delensing factor reaches 48 ±1 % . For low-noise surveys, our delensing maps, which cover much of the sky, can thus improve constraints on the tensor-to-scalar ratio (r ) by nearly a factor of 2. The delensing tracer maps are made publicly available, and we encourage their use in ongoing and upcoming B -mode surveys.

Effects of differential mobility on biased diffusion of two species

International Nuclear Information System (INIS)

Hipolito, R S; Zia, R K P; Schmittmann, B

2003-01-01

Using simulations and a simple mean-field theory, we investigate jamming transitions in a two-species lattice gas under non-equilibrium steady-state conditions. The two types of particles diffuse with different mobilities on a square lattice, subject to an excluded volume constraint and biased in opposite directions. Varying filling fraction, differential mobility and drive, we map out the phase diagram, identifying first order and continuous transitions between a free-flowing disordered and a spatially inhomogeneous jammed phase. Ordered structures are observed to drift, with a characteristic velocity, in the direction of the more mobile species

Thermophysical Property Estimation by Transient Experiments: The Effect of a Biased Initial Temperature Distribution

Directory of Open Access Journals (Sweden)

Federico Scarpa

2015-01-01

Full Text Available The identification of thermophysical properties of materials in dynamic experiments can be conveniently performed by the inverse solution of the associated heat conduction problem (IHCP. The inverse technique demands the knowledge of the initial temperature distribution within the material. As only a limited number of temperature sensors (or no sensor at all are arranged inside the test specimen, the knowledge of the initial temperature distribution is affected by some uncertainty. This uncertainty, together with other possible sources of bias in the experimental procedure, will propagate in the estimation process and the accuracy of the reconstructed thermophysical property values could deteriorate. In this work the effect on the estimated thermophysical properties due to errors in the initial temperature distribution is investigated along with a practical method to quantify this effect. Furthermore, a technique for compensating this kind of bias is proposed. The method consists in including the initial temperature distribution among the unknown functions to be estimated. In this way the effect of the initial bias is removed and the accuracy of the identified thermophysical property values is highly improved.

Bond and Equity Home Bias and Foreign Bias: an International Study

OpenAIRE

VanPée, Rosanne; De Moor, Lieven

2012-01-01

In this paper we explore tentatively and formally the differences between bond and equity home bias and foreign bias based on one large scale dataset including developed and emerging markets for the period 2001 to 2010. We set the stage by tentatively and formally linking the diversion of bond and equity home bias in OECD countries to the increasing public debt issues under the form of government bonds i.e. the supply-driven argument. Unlike Fidora et al. (2007) we do not find that exchange r...

Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

Science.gov (United States)

Adler, Robert; Gu, Guojun; Huffman, George

2012-01-01

A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a

Decoupling Action Potential Bias from Cortical Local Field Potentials

Directory of Open Access Journals (Sweden)

Stephen V. David

2010-01-01

Full Text Available Neurophysiologists have recently become interested in studying neuronal population activity through local field potential (LFP recordings during experiments that also record the activity of single neurons. This experimental approach differs from early LFP studies because it uses high impendence electrodes that can also isolate single neuron activity. A possible complication for such studies is that the synaptic potentials and action potentials of the small subset of isolated neurons may contribute disproportionately to the LFP signal, biasing activity in the larger nearby neuronal population to appear synchronous and cotuned with these neurons. To address this problem, we used linear filtering techniques to remove features correlated with spike events from LFP recordings. This filtering procedure can be applied for well-isolated single units or multiunit activity. We illustrate the effects of this correction in simulation and on spike data recorded from primary auditory cortex. We find that local spiking activity can explain a significant portion of LFP power at most recording sites and demonstrate that removing the spike-correlated component can affect measurements of auditory tuning of the LFP.

Velocity bias induced by flow patterns around ADCPs and associated deployment platforms

Science.gov (United States)

Mueller, David S.

2015-01-01

Velocity measurements near the Acoustic Doppler Current Profiler (ADCP) are important for mapping surface currents, measuring velocity and discharge in shallow streams, and providing accurate estimates of discharge in the top unmeasured portion of the water column. Improvements to ADCP performance permit measurement of velocities much closer (5 cm) to the transducer than has been possible in the past (25 cm). Velocity profiles collected by the U.S. Geological Survey (USGS) with a 1200 kHz Rio Grande Zedhead ADCP in 2002 showed a negative bias in measured velocities near the transducers. On the basis of these results, the USGS initiated a study combining field, laboratory, and numerical modeling data to assess the effect of flow patterns caused by flow around the ADCP and deployment platforms on velocities measured near the transducers. This ongoing study has shown that the negative bias observed in the field is due to the flow pattern around the ADCP. The flow pattern around an ADCP violates the basic assumption of flow homogeneity required for an accurate three-dimensional velocity solution. Results, to date (2014), have indicated velocity biases within the measurable profile, due to flow disturbance, for the TRDI 1200 kHz Rio Grande Zedhead and the SonTek RiverSurveyor M9 ADCPs. The flow speed past the ADCP, the mount and the deployment platform have also been shown to play an important role in the magnitude and extent of the velocity bias.

Bias caused by water adsorption in hourly PM measurements

Directory of Open Access Journals (Sweden)

G. Kiss

2017-07-01

Full Text Available Beta-attenuation monitors are used worldwide to monitor PM mass concentration with high temporal resolution. Hourly PM10 and PM2. 5 dry mass concentrations are publicly available with the tacit assumption that water is effectively removed prior to the measurement. However, as both the filter material of the monitor and the aerosol particles are capable of retaining a significant amount of water even at low relative humidities, the basic assumption may not be valid, resulting in significant bias in reported PM10 and PM2. 5 concentrations. Here we show that in PM10 measurement, particle-free air can produce apparent hourly average PM concentrations in the range of −13–+21 µg m−3 under conditions of fluctuating relative humidity. Positive and negative apparent readings are observed with increasing and decreasing relative humidities, respectively. Similar phenomena have been observed when the instrument filter was previously loaded with atmospheric aerosol. As a result the potential measurement biases in hourly readings arising from the interaction with water may be in the range of −53… + 69 %.

Galaxy bias and non-linear structure formation in general relativity

International Nuclear Information System (INIS)

Baldauf, Tobias; Seljak, Uroš; Senatore, Leonardo; Zaldarriaga, Matias

2011-01-01

Length scales probed by the large scale structure surveys are becoming closer and closer to the horizon scale. Further, it has been recently understood that non-Gaussianity in the initial conditions could show up in a scale dependence of the bias of galaxies at the largest possible distances. It is therefore important to take General Relativistic effects into account. Here we provide a General Relativistic generalization of the bias that is valid both for Gaussian and for non-Gaussian initial conditions. The collapse of objects happens on very small scales, while long-wavelength modes are always in the quasi linear regime. Around every small collapsing region, it is therefore possible to find a reference frame that is valid for arbitrary times and where the space time is almost flat: the Fermi frame. Here the Newtonian approximation is applicable and the equations of motion are the ones of the standard N-body codes. The effects of long-wavelength modes are encoded in the mapping from the cosmological frame to the local Fermi frame. At the level of the linear bias, the effect of the long-wavelength modes on the dynamics of the short scales is all encoded in the local curvature of the Universe, which allows us to define a General Relativistic generalization of the bias in the standard Newtonian setting. We show that the bias due to this effect goes to zero as the square of the ratio between the physical wavenumber and the Hubble scale for modes longer than the horizon, confirming the intuitive picture that modes longer than the horizon do not have any dynamical effect. On the other hand, the bias due to non-Gaussianities does not need to vanish for modes longer than the Hubble scale, and for non-Gaussianities of the local kind it goes to a constant. As a further application of our setup, we show that it is not necessary to perform large N-body simulations to extract information about long-wavelength modes: N-body simulations can be done on small scales and long

Topological visual mapping in robotics.

Science.gov (United States)

Romero, Anna; Cazorla, Miguel

2012-08-01

A key problem in robotics is the construction of a map from its environment. This map could be used in different tasks, like localization, recognition, obstacle avoidance, etc. Besides, the simultaneous location and mapping (SLAM) problem has had a lot of interest in the robotics community. This paper presents a new method for visual mapping, using topological instead of metric information. For that purpose, we propose prior image segmentation into regions in order to group the extracted invariant features in a graph so that each graph defines a single region of the image. Although others methods have been proposed for visual SLAM, our method is complete, in the sense that it makes all the process: it presents a new method for image matching; it defines a way to build the topological map; and it also defines a matching criterion for loop-closing. The matching process will take into account visual features and their structure using the graph transformation matching (GTM) algorithm, which allows us to process the matching and to remove out the outliers. Then, using this image comparison method, we propose an algorithm for constructing topological maps. During the experimentation phase, we will test the robustness of the method and its ability constructing topological maps. We have also introduced new hysteresis behavior in order to solve some problems found building the graph.

Foreground removal from Planck Sky Model temperature maps using a MLP neural network

DEFF Research Database (Denmark)

Nørgaard-Nielsen, Hans Ulrik; Hebert, K.

2009-01-01

with no systematic errors. To demonstrate the feasibility of a simple multilayer perceptron (MLP) neural network for extracting the CMB temperature signal, we have analyzed a specific data set, namely the Planck Sky Model maps, developed for evaluation of different component separation methods before including them...... in the Planck data analysis pipeline. It is found that a MLP neural network can provide a CMB map of about 80% of the sky to a very high degree uncorrelated with the foreground components. Also the derived power spectrum shows little evidence for systematic errors....

Cognitive Bias in Systems Verification

Science.gov (United States)

Larson, Steve

2012-01-01

Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.

Bias correction of daily precipitation projected by the CORDEX-Africa ensemble for a sparsely gauged region in West Africa with regionalized distribution parameters

Science.gov (United States)

Lorenz, Manuel; Bliefernicht, Jan; Laux, Patrick; Kunstmann, Harald

2017-04-01

Reliable estimates of future climatic conditions are indispensable for the sustainable planning of agricultural activities in West Africa. Precipitation time series of regional climate models (RCMs) typically exhibit a bias in the distribution of both rainfall intensities and wet day frequencies. Furthermore, the annual and monthly sums of precipitation may remarkably vary from the observations in this region. As West Africa experiences a distinct rainy season, sowing dates are oftentimes planned based on the beginning of this rainfall period. A biased representation of the annual cycle of precipitation in the uncorrected RCMs can therefore lead to crop failure. The precipitation ensemble, obtained from the Coordinated Downscaling Experiment CORDEX-Africa, was bias-corrected for the study region in West Africa (extending approximately 343,358 km2) which covers large parts of Burkina Faso, Ghana and Benin. In oder to debias the RCM precipitation simulations, a Quantile-Mapping method was applied to the historical period 1950-2005. For the RCM future projections (2006-2100), the Double-Quantile-Mapping procedure was chosen. This method makes use of the shift in the distribution function of the future precipitation values which allows to incorporate the climate change signal of the RCM projections into the bias correction. As large areas of the study region are ungauged, the assignment of the information from the nearest station to the ungauged location would lead to sharp changes in the estimated statistics from one location to another. Thus, the distribution parameters needed for the Quantile-Mapping were estimated by Kriging the distribution parameters of the available measurement stations. This way it is possible to obtain reasonable estimates of the expected distribution of precipitation at ungauged locations. The presentation will illustrate some aspects and trade-offs in the distribution parameter interpolation as well as an analysis of the uncertainties of the

Biases in categorization

NARCIS (Netherlands)

Das-Smaal, E.A.

1990-01-01

On what grounds can we conclude that an act of categorization is biased? In this chapter, it is contended that in the absence of objective norms of what categories actually are, biases in categorization can only be specified in relation to theoretical understandings of categorization. Therefore, the

The Fungible Audio-Visual Mapping and its Experience

Directory of Open Access Journals (Sweden)

Adriana Sa

2014-12-01

Full Text Available This article draws a perceptual approach to audio-visual mapping. Clearly perceivable cause and effect relationships can be problematic if one desires the audience to experience the music. Indeed perception would bias those sonic qualities that fit previous concepts of causation, subordinating other sonic qualities, which may form the relations between the sounds themselves. The question is, how can an audio-visual mapping produce a sense of causation, and simultaneously confound the actual cause-effect relationships. We call this a fungible audio-visual mapping. Our aim here is to glean its constitution and aspect. We will report a study, which draws upon methods from experimental psychology to inform audio-visual instrument design and composition. The participants are shown several audio-visual mapping prototypes, after which we pose quantitative and qualitative questions regarding their sense of causation, and their sense of understanding the cause-effect relationships. The study shows that a fungible mapping requires both synchronized and seemingly non-related components – sufficient complexity to be confusing. As the specific cause-effect concepts remain inconclusive, the sense of causation embraces the whole. 

Carbon monoxide climatology derived from the trajectory mapping of global MOZAIC-IAGOS data

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M. K. Osman

2016-08-01

Full Text Available A three-dimensional gridded climatology of carbon monoxide (CO has been developed by trajectory mapping of global MOZAIC-IAGOS in situ measurements from commercial aircraft data. CO measurements made during aircraft ascent and descent, comprising nearly 41 200 profiles at 148 airports worldwide from December 2001 to December 2012, are used. Forward and backward trajectories are calculated from meteorological reanalysis data in order to map the CO measurements to other locations and so to fill in the spatial domain. This domain-filling technique employs 15 800 000 calculated trajectories to map otherwise sparse MOZAIC-IAGOS data into a quasi-global field. The resulting trajectory-mapped CO data set is archived monthly from 2001 to 2012 on a grid of 5° longitude  ×  5° latitude  ×  1 km altitude, from the surface to 14 km altitude.The mapping product has been carefully evaluated, firstly by comparing maps constructed using only forward trajectories and using only backward trajectories. The two methods show similar global CO distribution patterns. The magnitude of their differences is most commonly 10 % or less and found to be less than 30 % for almost all cases. Secondly, the method has been validated by comparing profiles for individual airports with those produced by the mapping method when data from that site are excluded. While there are larger differences below 2 km, the two methods agree very well between 2 and 10 km with the magnitude of biases within 20 %. Finally, the mapping product is compared with global MOZAIC-IAGOS cruise-level data, which were not included in the trajectory-mapped data set, and with independent data from the NOAA aircraft flask sampling program. The trajectory-mapped MOZAIC-IAGOS CO values show generally good agreement with both independent data sets.Maps are also compared with version 6 data from the Measurements Of Pollution In The Troposphere (MOPITT satellite instrument

High-resolution three-dimensional mapping of semiconductor dopant potentials

DEFF Research Database (Denmark)

Twitchett, AC; Yates, TJV; Newcomb, SB

2007-01-01

Semiconductor device structures are becoming increasingly three-dimensional at the nanometer scale. A key issue that must be addressed to enable future device development is the three-dimensional mapping of dopant distributions, ideally under "working conditions". Here we demonstrate how a combin......Semiconductor device structures are becoming increasingly three-dimensional at the nanometer scale. A key issue that must be addressed to enable future device development is the three-dimensional mapping of dopant distributions, ideally under "working conditions". Here we demonstrate how...... a combination of electron holography and electron tomography can be used to determine quantitatively the three-dimensional electrostatic potential in an electrically biased semiconductor device with nanometer spatial resolution....

2-D mapping of ICRF-induced SOL perturbations in Tore Supra tokamak

International Nuclear Information System (INIS)

Colas, L.; Gunn, J.P.; Nanobashvili, I.; Petrzilka, V.; Goniche, M.; Ekedahl, A.; Heuraux, S.; Joffrin, E.; Saint-Laurent, F.; Balorin, C.; Lowry, C.; Basiuk, V.

2007-01-01

ICRF-induced SOL modifications are mapped for the first time in 2-D around Tore Supra ICRF antennas using reciprocating Langmuir probes. When probe heads are magnetically connected to powered antennas, radical modifications of floating potentials V float , effective temperatures T eff and ion saturation currents are observed. V float perturbations are located radially near antenna limiters, with a typical extension 2 cm. Poloidally they are locally minimal near the equatorial plane, and maximal near antenna box corners. Two possible interpretations for increased T eff are proposed: localised electron heating and RF loop voltage induced along probe circuit. Both interpretations rely on the generation of parallel RF fields by parallel RF currents on the antenna structure. The topology of such currents could explain the 2-D structure of T eff maps. Both interpretations also imply a positive DC biasing of the antenna environment. Differential biasing of nearby flux tubes drives DC E x B 0 convection that could explain 2-D density patterns

Cognitive bias measurement and social anxiety disorder: Correlating self-report data and attentional bias

Directory of Open Access Journals (Sweden)

Alexander Miloff

2015-09-01

Full Text Available Social anxiety disorder (SAD and attentional bias are theoretically connected in cognitive behavioral therapeutic models. In fact, there is an emerging field focusing on modifying attentional bias as a stand-alone treatment. However, it is unclear to what degree these attentional biases are present before commencing treatment. The purpose of this study was to measure pre-treatment attentional bias in 153 participants diagnosed with SAD using a home-based Internet version of the dot-probe paradigm. Results showed no significant correlation for attentional bias (towards or away from negative words or faces and the self-rated version of the Liebowitz Social Anxiety Scale (LSAS-SR. However, two positive correlations were found for the secondary measures Generalized Anxiety Disorder 7 (GAD-7 and Patient Health Questionnaire 9 (PHQ-9. These indicated that those with elevated levels of anxiety and depression had a higher bias towards negative faces in neutral–negative and positive–negative valence combinations, respectively. The unreliability of the dot-probe paradigm and home-based Internet delivery are discussed to explain the lack of correlations between LSAS-SR and attentional bias. Changes to the dot-probe task are suggested that could improve reliability.

Subsurface imaging of carbon nanotube networks in polymers with DC-biased multifrequency dynamic atomic force microscopy.

Science.gov (United States)

Thompson, Hank T; Barroso-Bujans, Fabienne; Herrero, Julio Gomez; Reifenberger, Ron; Raman, Arvind

2013-04-05

The characterization of dispersion and connectivity of carbon nanotube (CNT) networks inside polymers is of great interest in polymer nanocomposites in new material systems, organic photovoltaics, and in electrodes for batteries and supercapacitors. We focus on a technique using amplitude modulation atomic force microscopy (AM-AFM) in the attractive regime of operation, using both single and dual mode excitation, which upon the application of a DC tip bias voltage allows, via the phase channel, the in situ, nanoscale, subsurface imaging of CNT networks dispersed in a polymer matrix at depths of 10-100 nm. We present an in-depth study of the origins of phase contrast in this technique and demonstrate that an electrical energy dissipation mechanism in the Coulomb attractive regime is key to the formation of the phase contrast which maps the spatial variations in the local capacitance and resistance due to the CNT network. We also note that dual frequency excitation can, under some conditions, improve the contrast for such samples. These methods open up the possibility for DC-biased amplitude modulation AFM to be used for mapping the variations in local capacitance and resistance in nanocomposites with conducting networks.

Threat bias, not negativity bias, underpins differences in political ideology.

Science.gov (United States)

Lilienfeld, Scott O; Latzman, Robert D

2014-06-01

Although disparities in political ideology are rooted partly in dispositional differences, Hibbing et al.'s analysis paints with an overly broad brush. Research on the personality correlates of liberal-conservative differences points not to global differences in negativity bias, but to differences in threat bias, probably emanating from differences in fearfulness. This distinction bears implications for etiological research and persuasion efforts.

Unbiased methods for removing systematics from galaxy clustering measurements

Science.gov (United States)

Elsner, Franz; Leistedt, Boris; Peiris, Hiranya V.

2016-02-01

Measuring the angular clustering of galaxies as a function of redshift is a powerful method for extracting information from the three-dimensional galaxy distribution. The precision of such measurements will dramatically increase with ongoing and future wide-field galaxy surveys. However, these are also increasingly sensitive to observational and astrophysical contaminants. Here, we study the statistical properties of three methods proposed for controlling such systematics - template subtraction, basic mode projection, and extended mode projection - all of which make use of externally supplied template maps, designed to characterize and capture the spatial variations of potential systematic effects. Based on a detailed mathematical analysis, and in agreement with simulations, we find that the template subtraction method in its original formulation returns biased estimates of the galaxy angular clustering. We derive closed-form expressions that should be used to correct results for this shortcoming. Turning to the basic mode projection algorithm, we prove it to be free of any bias, whereas we conclude that results computed with extended mode projection are biased. Within a simplified setup, we derive analytical expressions for the bias and discuss the options for correcting it in more realistic configurations. Common to all three methods is an increased estimator variance induced by the cleaning process, albeit at different levels. These results enable unbiased high-precision clustering measurements in the presence of spatially varying systematics, an essential step towards realizing the full potential of current and planned galaxy surveys.

Validation of satellite SAR offshore wind speed maps to in-situ data, microscale and mesoscale model results

DEFF Research Database (Denmark)

Hasager, C.B.; Astrup, Poul; Barthelmie, R.J.

2002-01-01

the assumption of no error in the SAR wind speed maps and for an uncertainty of ± 10% at a confidence level of 90%. Around 100 satellite SAR scenes may be available for some sites on Earth but far few at other sites. Currently the numberof available satellite SAR scenes is increasing rapidly with ERS-2, RADARSAT......A validation study has been performed in order to investigate the precision and accuracy of the satellite-derived ERS-2 SAR wind products in offshore regions. The overall project goal is to develop a method for utilizing the satellite wind speed maps foroffshore wind resources, e.g. in future...... band in which the SAR wind speed observations have a strong negative bias. The bathymetry of Horns Rev combined with tidal currents give rise to bias in the SAR wind speed maps near areas of shallow, complex bottom topography in some cases. Atotal of 16 cases were analyzed for Horns Rev. For Maddalena...

Good practices for quantitative bias analysis.

Science.gov (United States)

Lash, Timothy L; Fox, Matthew P; MacLehose, Richard F; Maldonado, George; McCandless, Lawrence C; Greenland, Sander

2014-12-01

Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias analyses have been known for decades, and there have been calls for more widespread use for nearly as long. There was a time when some believed that bias analyses were rarely undertaken because the methods were not widely known and because automated computing tools were not readily available to implement the methods. These shortcomings have been largely resolved. We must, therefore, contemplate other barriers to implementation. One possibility is that practitioners avoid the analyses because they lack confidence in the practice of bias analysis. The purpose of this paper is therefore to describe what we view as good practices for applying quantitative bias analysis to epidemiological data, directed towards those familiar with the methods. We focus on answering questions often posed to those of us who advocate incorporation of bias analysis methods into teaching and research. These include the following. When is bias analysis practical and productive? How does one select the biases that ought to be addressed? How does one select a method to model biases? How does one assign values to the parameters of a bias model? How does one present and interpret a bias analysis?. We hope that our guide to good practices for conducting and presenting bias analyses will encourage

Classical mapping for Hubbard operators: Application to the double-Anderson model

Energy Technology Data Exchange (ETDEWEB)

Li, Bin; Miller, William H. [Department of Chemistry and Kenneth S. Pitzer Center for Theoretical Chemistry, University of California, and Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Levy, Tal J.; Rabani, Eran [School of Chemistry, The Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978 (Israel)

2014-05-28

A classical Cartesian mapping for Hubbard operators is developed to describe the nonequilibrium transport of an open quantum system with many electrons. The mapping of the Hubbard operators representing the many-body Hamiltonian is derived by using analogies from classical mappings of boson creation and annihilation operators vis-à-vis a coherent state representation. The approach provides qualitative results for a double quantum dot array (double Anderson impurity model) coupled to fermionic leads for a range of bias voltages, Coulomb couplings, and hopping terms. While the width and height of the conduction peaks show deviations from the master equation approach considered to be accurate in the limit of weak system-leads couplings and high temperatures, the Hubbard mapping captures all transport channels involving transition between many electron states, some of which are not captured by approximate nonequilibrium Green function closures.

Hindsight bias and outcome bias in the social construction of medical negligence: a review.

Science.gov (United States)

Hugh, Thomas B; Dekker, Sidney W A

2009-05-01

Medical negligence has been the subject of much public debate in recent decades. Although the steep increase in the frequency and size of claims against doctors at the end of the last century appears to have plateaued, in Australia at least, medical indemnity costs and consequences are still a matter of concern for doctors, medical defence organisations and governments in most developed countries. Imprecision in the legal definition of negligence opens the possibility that judgments of this issue at several levels may be subject to hindsight and outcome bias. Hindsight bias relates to the probability of an adverse event perceived by a retrospective observer ("I would have known it was going to happen"), while outcome bias is a largely subconscious cognitive distortion produced by the observer's knowledge of the adverse outcome. This review examines the relevant legal, medical, psychological and sociological literature on the operation of these pervasive and universal biases in the retrospective evaluation of adverse events. A finding of medical negligence is essentially an after-the-event social construction and is invariably affected by hindsight bias and knowledge of the adverse outcome. Such biases obviously pose a threat to the fairness of judgments. A number of debiasing strategies have been suggested but are relatively ineffective because of the universality and strength of these biases and the inherent difficulty of concealing from expert witnesses knowledge of the outcome. Education about the effect of the biases is therefore important for lawyers, medical expert witnesses and the judiciary.

Photovoltaic Bias Generator

Science.gov (United States)

2018-02-01

Department of the Army position unless so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an... Interior view of the photovoltaic bias generator showing wrapped-wire side of circuit board...3 Fig. 4 Interior view of the photovoltaic bias generator showing component side of circuit board

Bias-correction in vector autoregressive models

DEFF Research Database (Denmark)

Engsted, Tom; Pedersen, Thomas Quistgaard

2014-01-01

We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study......, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable...... improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find...

Analysis of Item-Level Bias in the Bayley-III Language Subscales: The Validity and Utility of Standardized Language Assessment in a Multilingual Setting.

Science.gov (United States)

Goh, Shaun K Y; Tham, Elaine K H; Magiati, Iliana; Sim, Litwee; Sanmugam, Shamini; Qiu, Anqi; Daniel, Mary L; Broekman, Birit F P; Rifkin-Graboi, Anne

2017-09-18

The purpose of this study was to improve standardized language assessments among bilingual toddlers by investigating and removing the effects of bias due to unfamiliarity with cultural norms or a distributed language system. The Expressive and Receptive Bayley-III language scales were adapted for use in a multilingual country (Singapore). Differential item functioning (DIF) was applied to data from 459 two-year-olds without atypical language development. This involved investigating if the probability of success on each item varied according to language exposure while holding latent language ability, gender, and socioeconomic status constant. Associations with language, behavioral, and emotional problems were also examined. Five of 16 items showed DIF, 1 of which may be attributed to cultural bias and another to a distributed language system. The remaining 3 items favored toddlers with higher bilingual exposure. Removal of DIF items reduced associations between language scales and emotional and language problems, but improved the validity of the expressive scale from poor to good. Our findings indicate the importance of considering cultural and distributed language bias in standardized language assessments. We discuss possible mechanisms influencing performance on items favoring bilingual exposure, including the potential role of inhibitory processing.

Bias versus bias: harnessing hindsight to reveal paranormal belief change beyond demand characteristics.

Science.gov (United States)

Kane, Michael J; Core, Tammy J; Hunt, R Reed

2010-04-01

Psychological change is difficult to assess, in part because self-reported beliefs and attitudes may be biased or distorted. The present study probed belief change, in an educational context, by using the hindsight bias to counter another bias that generally plagues assessment of subjective change. Although research has indicated that skepticism courses reduce paranormal beliefs, those findings may reflect demand characteristics (biases toward desired, skeptical responses). Our hindsight-bias procedure circumvented demand by asking students, following semester-long skepticism (and control) courses, to recall their precourse levels of paranormal belief. People typically remember themselves as previously thinking, believing, and acting as they do now, so current skepticism should provoke false recollections of previous skepticism. Given true belief change, therefore, skepticism students should have remembered themselves as having been more skeptical than they were. They did, at least about paranormal topics that were covered most extensively in the course. Our findings thus show hindsight to be useful in evaluating cognitive change beyond demand characteristics.

Process-conditioned bias correction for seasonal forecasting: a case-study with ENSO in Peru

Science.gov (United States)

Manzanas, R.; Gutiérrez, J. M.

2018-05-01

This work assesses the suitability of a first simple attempt for process-conditioned bias correction in the context of seasonal forecasting. To do this, we focus on the northwestern part of Peru and bias correct 1- and 4-month lead seasonal predictions of boreal winter (DJF) precipitation from the ECMWF System4 forecasting system for the period 1981-2010. In order to include information about the underlying large-scale circulation which may help to discriminate between precipitation affected by different processes, we introduce here an empirical quantile-quantile mapping method which runs conditioned on the state of the Southern Oscillation Index (SOI), which is accurately predicted by System4 and is known to affect the local climate. Beyond the reduction of model biases, our results show that the SOI-conditioned method yields better ROC skill scores and reliability than the raw model output over the entire region of study, whereas the standard unconditioned implementation provides no added value for any of these metrics. This suggests that conditioning the bias correction on simple but well-simulated large-scale processes relevant to the local climate may be a suitable approach for seasonal forecasting. Yet, further research on the suitability of the application of similar approaches to the one considered here for other regions, seasons and/or variables is needed.

Robust, open-source removal of systematics in Kepler data

Science.gov (United States)

Aigrain, S.; Parviainen, H.; Roberts, S.; Reece, S.; Evans, T.

2017-10-01

We present ARC2 (Astrophysically Robust Correction 2), an open-source python-based systematics-correction pipeline, to correct for the Kepler prime mission long-cadence light curves. The ARC2 pipeline identifies and corrects any isolated discontinuities in the light curves and then removes trends common to many light curves. These trends are modelled using the publicly available co-trending basis vectors, within an (approximate) Bayesian framework with 'shrinkage' priors to minimize the risk of overfitting and the injection of any additional noise into the corrected light curves, while keeping any astrophysical signals intact. We show that the ARC2 pipeline's performance matches that of the standard Kepler PDC-MAP data products using standard noise metrics, and demonstrate its ability to preserve astrophysical signals using injection tests with simulated stellar rotation and planetary transit signals. Although it is not identical, the ARC2 pipeline can thus be used as an open-source alternative to PDC-MAP, whenever the ability to model the impact of the systematics removal process on other kinds of signal is important.

Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

Science.gov (United States)

Hakala, Kirsti; Addor, Nans; Seibert, Jan

2017-04-01

streamflow under the climate scenarios RCP4.5 and RCP8.5. We utilize two techniques for correcting biases in the climate model output: quantile mapping and a new method, frequency bias correction. The FBC method matches the frequencies between observed and GCM-RCM data. In this way, it can be used to correct for all time scales, which is a known limitation of quantile mapping. A novel approach for the evaluation of the climate simulations and bias correction methods was then applied. Streamflow can be thought of as the "great integrator" of uncertainties. The ability, or the lack thereof, to correctly simulate streamflow is a way to assess the realism of the bias-corrected climate simulations. Long-term monthly mean as well as high and low flow metrics are used to evaluate the realism of the simulations under current climate and to gauge the impacts of climate change on streamflow. Preliminary results show that under present climate, calibration of the hydrological model comprises of a much smaller band of uncertainty in the modeling chain as compared to the bias correction of the GCM-RCMs. Therefore, for future time periods, we expect the bias correction of climate model data to have a greater influence on projected changes in streamflow than the calibration of the hydrological model.

Gender-biased Appropriation of Space?. GI_Forum|GI_Forum 2015 – Geospatial Minds for Society|

OpenAIRE

Groß, Christian; Gryl, Inga

2016-01-01

Several studies indicate gender differences in spatial orientation, map reading, and the way people appropriate spaces for everyday action. Thereby, the most important factor of gender differences in spatially related abilities is socialization. Gender roles and differences are already present in primary school age, and gender differences in the appropriation of space may lead to unequal chances of societal participation. Therefore, it is worth drawing a focus on gender-biased education in pr...

A landslide susceptibility map of Africa

Science.gov (United States)

Broeckx, Jente; Vanmaercke, Matthias; Duchateau, Rica; Poesen, Jean

2017-04-01

Studies on landslide risks and fatalities indicate that landslides are a global threat to humans, infrastructure and the environment, certainly in Africa. Nonetheless our understanding of the spatial patterns of landslides and rockfalls on this continent is very limited. Also in global landslide susceptibility maps, Africa is mostly underrepresented in the inventories used to construct these maps. As a result, predicted landslide susceptibilities remain subject to very large uncertainties. This research aims to produce a first continent-wide landslide susceptibility map for Africa, calibrated with a well-distributed landslide dataset. As a first step, we compiled all available landslide inventories for Africa. This data was supplemented by additional landslide mapping with Google Earth in underrepresented regions. This way, we compiled 60 landslide inventories from the literature (ca. 11000 landslides) and an additional 6500 landslides through mapping in Google Earth (including 1500 rockfalls). Various environmental variables such as slope, lithology, soil characteristics, land use, precipitation and seismic activity, were investigated for their significance in explaining the observed spatial patterns of landslides. To account for potential mapping biases in our dataset, we used Monte Carlo simulations that selected different subsets of mapped landslides, tested the significance of the considered environmental variables and evaluated the performance of the fitted multiple logistic regression model against another subset of mapped landslides. Based on these analyses, we constructed two landslide susceptibility maps for Africa: one for all landslide types and one excluding rockfalls. In both maps, topography, lithology and seismic activity were the most significant variables. The latter factor may be surprising, given the overall limited degree of seismicity in Africa. However, its significance indicates that frequent seismic events may serve as in important

Toward a synthesis of cognitive biases: how noisy information processing can bias human decision making.

Science.gov (United States)

Hilbert, Martin

2012-03-01

A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelated cognitive decision-making biases. During the past 6 decades, hundreds of empirical studies have resulted in a variety of rules of thumb that specify how humans systematically deviate from what is normatively expected from their decisions. Several complementary generative mechanisms have been proposed to explain those cognitive biases. Here it is suggested that (at least) 8 of these empirically detected decision-making biases can be produced by simply assuming noisy deviations in the memory-based information processes that convert objective evidence (observations) into subjective estimates (decisions). An integrative framework is presented to show how similar noise-based mechanisms can lead to conservatism, the Bayesian likelihood bias, illusory correlations, biased self-other placement, subadditivity, exaggerated expectation, the confidence bias, and the hard-easy effect. Analytical tools from information theory are used to explore the nature and limitations that characterize such information processes for binary and multiary decision-making exercises. The ensuing synthesis offers formal mathematical definitions of the biases and their underlying generative mechanism, which permits a consolidated analysis of how they are related. This synthesis contributes to the larger goal of creating a coherent picture that explains the relations among the myriad of seemingly unrelated biases and their potential psychological generative mechanisms. Limitations and research questions are discussed.

3D mapping of turbulence: a laboratory experiment

Science.gov (United States)

Le Louarn, Miska; Dainty, Christopher; Paterson, Carl; Tallon, Michel

2000-07-01

In this paper, we present the first experimental results of the 3D mapping method. 3D mapping of turbulence is a method to remove the cone effect with multiple laser guide stars and multiple deformable mirrors. A laboratory experiment was realized to verify the theoretical predictions. The setup consisted of two turbulent phase screens (made with liquid crystal devices) and a Shack-Hartmann wavefront sensor. We describe the interaction matrix involved in reconstructing Zernike commands for multiple deformable mirror from the slope measurements made from laser guide stars. It is shown that mirror commands can indeed be reconstructed with the 3D mapping method. Limiting factors of the method, brought to light by this experiment are discussed.

Experimental determination of isotope enrichment factors – bias from mass removal by repetitive sampling

DEFF Research Database (Denmark)

Buchner, Daniel; Jin, Biao; Ebert, Karin

2017-01-01

to account for mass removal and for volatilization into the headspace. In this study we use both synthetic and experimental data to demonstrate that the determination of ε-values according to current correction methods is prone to considerable systematic errors even in well-designed experimental setups....... Application of inappropriate methods may lead to incorrect and inconsistent ε-values entailing misinterpretations regarding the processes underlying isotope fractionation. In fact, our results suggest that artifacts arising from inappropriate data evaluation might contribute to the variability of published ε...

Mood-congruent attention and memory bias in dysphoria: Exploring the coherence among information-processing biases.

Science.gov (United States)

Koster, Ernst H W; De Raedt, Rudi; Leyman, Lemke; De Lissnyder, Evi

2010-03-01

Recent studies indicate that depression is characterized by mood-congruent attention bias at later stages of information-processing. Moreover, depression has been associated with enhanced recall of negative information. The present study tested the coherence between attention and memory bias in dysphoria. Stable dysphoric (n = 41) and non-dysphoric (n = 41) undergraduates first performed a spatial cueing task that included negative, positive, and neutral words. Words were presented for 250 ms under conditions that allowed or prevented elaborate processing. Memory for the words presented in the cueing task was tested using incidental free recall. Dysphoric individuals exhibited an attention bias for negative words in the condition that allowed elaborate processing, with the attention bias for negative words predicting free recall of negative words. Results demonstrate the coherence of attention and memory bias in dysphoric individuals and provide suggestions on the influence of attention bias on further processing of negative material. 2009 Elsevier Ltd. All rights reserved.

Bias in clinical intervention research

DEFF Research Database (Denmark)

Gluud, Lise Lotte

2006-01-01

Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical...... evidence is needed to evaluate their effects on the extent and direction of bias. This narrative review summarizes the findings of methodological studies on the influence of bias in clinical trials. A number of methodological studies suggest that lack of adequate randomization in published trial reports...

Stimulus-Driven Attention, Threat Bias, and Sad Bias in Youth with a History of an Anxiety Disorder or Depression.

Science.gov (United States)

Sylvester, Chad M; Hudziak, James J; Gaffrey, Michael S; Barch, Deanna M; Luby, Joan L

2016-02-01

Attention biases towards threatening and sad stimuli are associated with pediatric anxiety and depression, respectively. The basic cognitive mechanisms associated with attention biases in youth, however, remain unclear. Here, we tested the hypothesis that threat bias (selective attention for threatening versus neutral stimuli) but not sad bias relies on stimulus-driven attention. We collected measures of stimulus-driven attention, threat bias, sad bias, and current clinical symptoms in youth with a history of an anxiety disorder and/or depression (ANX/DEP; n = 40) as well as healthy controls (HC; n = 33). Stimulus-driven attention was measured with a non-emotional spatial orienting task, while threat bias and sad bias were measured at a short time interval (150 ms) with a spatial orienting task using emotional faces and at a longer time interval (500 ms) using a dot-probe task. In ANX/DEP but not HC, early attention bias towards threat was negatively correlated with later attention bias to threat, suggesting that early threat vigilance was associated with later threat avoidance. Across all subjects, stimulus-driven orienting was not correlated with early threat bias but was negatively correlated with later threat bias, indicating that rapid stimulus-driven orienting is linked to later threat avoidance. No parallel relationships were detected for sad bias. Current symptoms of depression but not anxiety were related to decreased stimulus-driven attention. Together, these results are consistent with the hypothesis that threat bias but not sad bias relies on stimulus-driven attention. These results inform the design of attention bias modification programs that aim to reverse threat biases and reduce symptoms associated with pediatric anxiety and depression.

Stimulus-driven attention, threat bias, and sad bias in youth with a history of an anxiety disorder or depression

Science.gov (United States)

Sylvester, Chad M.; Hudziak, James J.; Gaffrey, Michael S.; Barch, Deanna M.; Luby, Joan L.

2015-01-01

Attention biases towards threatening and sad stimuli are associated with pediatric anxiety and depression, respectively. The basic cognitive mechanisms associated with attention biases in youth, however, remain unclear. Here, we tested the hypothesis that threat bias (selective attention for threatening versus neutral stimuli) but not sad bias relies on stimulus-driven attention. We collected measures of stimulus-driven attention, threat bias, sad bias, and current clinical symptoms in youth with a history of an anxiety disorder and/or depression (ANX/DEP; n=40) as well as healthy controls (HC; n=33). Stimulus-driven attention was measured with a non-emotional spatial orienting task, while threat bias and sad bias were measured at a short time interval (150 ms) with a spatial orienting task using emotional faces and at a longer time interval (500 ms) using a dot-probe task. In ANX/DEP but not HC, early attention bias towards threat was negatively correlated with later attention bias to threat, suggesting that early threat vigilance was associated with later threat avoidance. Across all subjects, stimulus-driven orienting was not correlated with early threat bias but was negatively correlated with later threat bias, indicating that rapid stimulus-driven orienting is linked to later threat avoidance. No parallel relationships were detected for sad bias. Current symptoms of depression but not anxiety were related to decreased stimulus-driven attention. Together, these results are consistent with the hypothesis that threat bias but not sad bias relies on stimulus-driven attention. These results inform the design of attention bias modification programs that aim to reverse threat biases and reduce symptoms associated with pediatric anxiety and depression. PMID:25702927

The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

Science.gov (United States)

Syfert, Mindy M; Smith, Matthew J; Coomes, David A

2013-01-01

Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.

Benefits of being biased!

Indian Academy of Sciences (India)

Administrator

Journal of Genetics, Vol. 83, No. 2, August 2004. Keywords. codon bias; alcohol dehydrogenase; Darwinian ... RESEARCH COMMENTARY. Benefits of being biased! SUTIRTH DEY*. Evolutionary Biology Laboratory, Evolutionary & Organismal Biology Unit,. Jawaharlal Nehru Centre for Advanced Scientific Research,.

Intrinsic functional brain mapping in reconstructed 4D magnetic susceptibility (χ) data space.

Science.gov (United States)

Chen, Zikuan; Calhoun, Vince

2015-02-15

By solving an inverse problem of T2*-weighted magnetic resonance imaging for a dynamic fMRI study, we reconstruct a 4D magnetic susceptibility source (χ) data space for intrinsic functional mapping. A 4D phase dataset is calculated from a 4D complex fMRI dataset. The background field and phase wrapping effect are removed by a Laplacian technique. A 3D χ source map is reconstructed from a 3D phase image by a computed inverse MRI (CIMRI) scheme. A 4D χ data space is reconstructed by repeating the 3D χ source reconstruction for each time point. A functional map is calculated by a temporal correlation between voxel signals in the 4D χ space and the timecourse of the task paradigm. With a finger-tapping experiment, we obtain two 3D functional mappings in the 4D magnitude data space and in the reconstructed 4D χ data space. We find that the χ-based functional mapping reveals co-occurrence of bidirectional responses in a 3D activation map that is different from the conventional magnitude-based mapping. The χ-based functional mapping can also be achieved by a 3D deconvolution of a phase activation map. Based on a subject experimental comparison, we show that the 4D χ tomography method could produce a similar χ activation map as obtained by the 3D deconvolution method. By removing the dipole effect and other fMRI technological contaminations, 4D χ tomography provides a 4D χ data space that allows a more direct and truthful functional mapping of a brain activity. Published by Elsevier B.V.

Biases in GNSS-Data Processing

Science.gov (United States)

Schaer, S. C.; Dach, R.; Lutz, S.; Meindl, M.; Beutler, G.

2010-12-01

Within the Global Positioning System (GPS) traditionally different types of pseudo-range measurements (P-code, C/A-code) are available on the first frequency that are tracked by the receivers with different technologies. For that reason, P1-C1 and P1-P2 Differential Code Biases (DCB) need to be considered in a GPS data processing with a mix of different receiver types. Since the Block IIR-M series of GPS satellites also provide C/A-code on the second frequency, P2-C2 DCB need to be added to the list of biases for maintenance. Potential quarter-cycle biases between different phase observables (specifically L2P and L2C) are another issue. When combining GNSS (currently GPS and GLONASS), careful consideration of inter-system biases (ISB) is indispensable, in particular when an adequate combination of individual GLONASS clock correction results from different sources (using, e.g., different software packages) is intended. Facing the GPS and GLONASS modernization programs and the upcoming GNSS, like the European Galileo and the Chinese Compass, an increasing number of types of biases is expected. The Center for Orbit Determination in Europe (CODE) is monitoring these GPS and GLONASS related biases for a long time based on RINEX files of the tracking network of the International GNSS Service (IGS) and in the frame of the data processing as one of the global analysis centers of the IGS. Within the presentation we give an overview on the stability of the biases based on the monitoring. Biases derived from different sources are compared. Finally, we give an outlook on the potential handling of such biases with the big variety of signals and systems expected in the future.

Performance evaluation and bias correction of DBS measurements for a 1290-MHz boundary layer profiler.

Science.gov (United States)

Liu, Zhao; Zheng, Chaorong; Wu, Yue

2018-02-01

Recently, the government installed a boundary layer profiler (BLP), which is operated under the Doppler beam swinging mode, in a coastal area of China, to acquire useful wind field information in the atmospheric boundary layer for several purposes. And under strong wind conditions, the performance of the BLP is evaluated. It is found that, even though the quality controlled BLP data show good agreement with the balloon observations, a systematic bias can always be found for the BLP data. For the low wind velocities, the BLP data tend to overestimate the atmospheric wind. However, with the increment of wind velocity, the BLP data show a tendency of underestimation. In order to remove the effect of poor quality data on bias correction, the probability distribution function of the differences between the two instruments is discussed, and it is found that the t location scale distribution is the most suitable probability model when compared to other probability models. After the outliers with a large discrepancy, which are outside of 95% confidence interval of the t location scale distribution, are discarded, the systematic bias can be successfully corrected using a first-order polynomial correction function. The methodology of bias correction used in the study not only can be referred for the correction of other wind profiling radars, but also can lay a solid basis for further analysis of the wind profiles.

Performance evaluation and bias correction of DBS measurements for a 1290-MHz boundary layer profiler

Science.gov (United States)

Liu, Zhao; Zheng, Chaorong; Wu, Yue

2018-02-01

Recently, the government installed a boundary layer profiler (BLP), which is operated under the Doppler beam swinging mode, in a coastal area of China, to acquire useful wind field information in the atmospheric boundary layer for several purposes. And under strong wind conditions, the performance of the BLP is evaluated. It is found that, even though the quality controlled BLP data show good agreement with the balloon observations, a systematic bias can always be found for the BLP data. For the low wind velocities, the BLP data tend to overestimate the atmospheric wind. However, with the increment of wind velocity, the BLP data show a tendency of underestimation. In order to remove the effect of poor quality data on bias correction, the probability distribution function of the differences between the two instruments is discussed, and it is found that the t location scale distribution is the most suitable probability model when compared to other probability models. After the outliers with a large discrepancy, which are outside of 95% confidence interval of the t location scale distribution, are discarded, the systematic bias can be successfully corrected using a first-order polynomial correction function. The methodology of bias correction used in the study not only can be referred for the correction of other wind profiling radars, but also can lay a solid basis for further analysis of the wind profiles.

Bias aware Kalman filters

DEFF Research Database (Denmark)

Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan

2006-01-01

This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections

Science.gov (United States)

Junk, J.; Ulber, B.; Vidal, S.; Eickermann, M.

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections.

Science.gov (United States)

Junk, J; Ulber, B; Vidal, S; Eickermann, M

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Removable control rod drive shaft guide

International Nuclear Information System (INIS)

Ales, M.W.; Brown, S.K.; Dixon, L.D.

1988-01-01

A removable control rod drive shaft guide is described for a control rod ''guide'' structure card, comprising: a. a substantially annular shaped main body portion having a central axial bore for receiving a control rod drive shaft and an upper exterior groove for receiving removal tooling; b. the main body portion having a reduced outer diameter at its lower section; c. a shoulder portion integral with the main body portion for supporting the main body portion on the guide structure card; d. the shoulder portion having a substantially radial bore and the reduced outer diameter lower section having a slot in alignment with the radial bore; e. a locking arm ''pivotaly'' mounted in the radial bore which protrudes into the slot and is movable between a first normal locking position for engaging the guide structure card and a second release position; f. a spring received within a second axial bore in the main body portion and biased against the locking arm for urging and locking arm into the first normal locking position; and g. a release tab at one end of the locking arm for moving the locking arm into the second release position

Measuring Agricultural Bias

DEFF Research Database (Denmark)

Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn

The measurement issue is the key issue in the literature on trade policy-induced agri-cultural price incentive bias. This paper introduces a general equilibrium effective rate of protection (GE-ERP) measure, which extends and generalizes earlier partial equilibrium nominal protection measures...... shares and intersectoral linkages - are crucial for determining the sign and magnitude of trade policy bias. The GE-ERP measure is therefore uniquely suited to capture the full impact of trade policies on agricultural price incentives. A Monte Carlo procedure confirms that the results are robust....... For the 15 sample countries, the results indicate that the agricultural price incentive bias, which was generally perceived to exist during the 1980s, was largely eliminated during the 1990s. The results also demonstrate that general equilibrium effects and country-specific characteristics - including trade...

Conductance maps of quantum rings due to a local potential perturbation.

Science.gov (United States)

Petrović, M D; Peeters, F M; Chaves, A; Farias, G A

2013-12-11

We performed a numerical simulation of the dynamics of a Gaussian shaped wavepacket inside a small sized quantum ring, smoothly connected to two leads and exposed to a perturbing potential of a biased atomic force microscope tip. Using the Landauer formalism, we calculated conductance maps of this system in the case of single and two subband transport. We explain the main features in the conductance maps as due to the AFM tip influence on the wavepacket phase and amplitude. In the presence of an external magnetic field, the tip modifies the ϕ0 periodic Aharonov-Bohm oscillation pattern into a ϕ0/2 periodic Al'tshuler-Aronov-Spivak oscillation pattern. Our results in the case of multiband transport suggest tip selectivity to higher subbands, making them more observable in the total conductance map.

Administrative bias in South Africa

Directory of Open Access Journals (Sweden)

E S Nwauche

2005-01-01

Full Text Available This article reviews the interpretation of section 6(2(aii of the Promotion of Administrative Justice Act which makes an administrator “biased or reasonably suspected of bias” a ground of judicial review. In this regard, the paper reviews the determination of administrative bias in South Africa especially highlighting the concept of institutional bias. The paper notes that inspite of the formulation of the bias ground of review the test for administrative bias is the reasonable apprehension test laid down in the case of President of South Africa v South African Rugby Football Union(2 which on close examination is not the same thing. Accordingly the paper urges an alternative interpretation that is based on the reasonable suspicion test enunciated in BTR Industries South Africa (Pty Ltd v Metal and Allied Workers Union and R v Roberts. Within this context, the paper constructs a model for interpreting the bias ground of review that combines the reasonable suspicion test as interpreted in BTR Industries and R v Roberts, the possibility of the waiver of administrative bias, the curative mechanism of administrative appeal as well as some level of judicial review exemplified by the jurisprudence of article 6(1 of the European Convention of Human Rights, especially in the light of the contemplation of the South African Magistrate Court as a jurisdictional route of judicial review.

Attention, interpretation, and memory biases in subclinical depression: a proof-of-principle test of the combined cognitive biases hypothesis.

Science.gov (United States)

Everaert, Jonas; Duyck, Wouter; Koster, Ernst H W

2014-04-01

Emotional biases in attention, interpretation, and memory are viewed as important cognitive processes underlying symptoms of depression. To date, there is a limited understanding of the interplay among these processing biases. This study tested the dependence of memory on depression-related biases in attention and interpretation. Subclinically depressed and nondepressed participants completed a computerized version of the scrambled sentences test (measuring interpretation bias) while their eye movements were recorded (measuring attention bias). This task was followed by an incidental free recall test of previously constructed interpretations (measuring memory bias). Path analysis revealed a good fit for the model in which selective orienting of attention was associated with interpretation bias, which in turn was associated with a congruent bias in memory. Also, a good fit was observed for a path model in which biases in the maintenance of attention and interpretation were associated with memory bias. Both path models attained a superior fit compared with path models without the theorized functional relations among processing biases. These findings enhance understanding of how mechanisms of attention and interpretation regulate what is remembered. As such, they offer support for the combined cognitive biases hypothesis or the notion that emotionally biased cognitive processes are not isolated mechanisms but instead influence each other. Implications for theoretical models and emotion regulation across the spectrum of depressive symptoms are discussed.

Picosecond lasers for tattoo removal: a systematic review.

Science.gov (United States)

Reiter, Ofer; Atzmony, Lihi; Akerman, Lehavit; Levi, Assi; Kershenovich, Ruben; Lapidoth, Moshe; Mimouni, Daniel

2016-09-01

Given that the pigment particles in tattoos have a relaxation time of tattoo removal. To systematically review the evidence regarding the effectiveness and safety of picosecond lasers for tattoo removal, Pubmed, Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov, and reference lists were searched for relevant trials. The primary outcome was >70 % clearance of tattoo pigment. Secondary outcomes were 90-100 % clearance of tattoo pigment, number of laser sessions required, and adverse effects. Eight trials were included, six with human participants (160 participants) and 2 with animal models. Seven of the eight trials explored the usage of either 755, 758, 795, 1064, or 1064/532-nm picosecond lasers for black and blue ink tattoos. In the human trials, 69-100 % of tattoos showed over 70 % clearance of pigment after 1-10 laser treatments. Reported side effects included pain, hyperpigmentation and hypopigmentation, blister formation and transient erythema, edema, and pinpoint bleeding. Included articles varied in type of laser investigated, mostly non-comparative studies and with a medium to high risk of bias. There is sparse evidence that picosecond lasers are more effective than their nanosecond counterparts for mainly black and blue ink tattoo removal, with minor side effects.

Preferences, country bias, and international trade

NARCIS (Netherlands)

S. Roy (Santanu); J.M.A. Viaene (Jean-Marie)

1998-01-01

textabstractAnalyzes international trade where consumer preferences exhibit country bias. Why country biases arise; How trade can occur in the presence of country bias; Implication for the pattern of trade and specialization.

Biases in casino betting

Directory of Open Access Journals (Sweden)

James Sundali

2006-07-01

Full Text Available We examine two departures of individual perceptions of randomness from probability theory: the hot hand and the gambler's fallacy, and their respective opposites. This paper's first contribution is to use data from the field (individuals playing roulette in a casino to demonstrate the existence and impact of these biases that have been previously documented in the lab. Decisions in the field are consistent with biased beliefs, although we observe significant individual heterogeneity in the population. A second contribution is to separately identify these biases within a given individual, then to examine their within-person correlation. We find a positive and significant correlation across individuals between hot hand and gambler's fallacy biases, suggesting a common (root cause of the two related errors. We speculate as to the source of this correlation (locus of control, and suggest future research which could test this speculation.

Imputation across genotyping arrays for genome-wide association studies: assessment of bias and a correction strategy.

Science.gov (United States)

Johnson, Eric O; Hancock, Dana B; Levy, Joshua L; Gaddis, Nathan C; Saccone, Nancy L; Bierut, Laura J; Page, Grier P

2013-05-01

A great promise of publicly sharing genome-wide association data is the potential to create composite sets of controls. However, studies often use different genotyping arrays, and imputation to a common set of SNPs has shown substantial bias: a problem which has no broadly applicable solution. Based on the idea that using differing genotyped SNP sets as inputs creates differential imputation errors and thus bias in the composite set of controls, we examined the degree to which each of the following occurs: (1) imputation based on the union of genotyped SNPs (i.e., SNPs available on one or more arrays) results in bias, as evidenced by spurious associations (type 1 error) between imputed genotypes and arbitrarily assigned case/control status; (2) imputation based on the intersection of genotyped SNPs (i.e., SNPs available on all arrays) does not evidence such bias; and (3) imputation quality varies by the size of the intersection of genotyped SNP sets. Imputations were conducted in European Americans and African Americans with reference to HapMap phase II and III data. Imputation based on the union of genotyped SNPs across the Illumina 1M and 550v3 arrays showed spurious associations for 0.2 % of SNPs: ~2,000 false positives per million SNPs imputed. Biases remained problematic for very similar arrays (550v1 vs. 550v3) and were substantial for dissimilar arrays (Illumina 1M vs. Affymetrix 6.0). In all instances, imputing based on the intersection of genotyped SNPs (as few as 30 % of the total SNPs genotyped) eliminated such bias while still achieving good imputation quality.

An inclusive taxonomy of behavioral biases

Directory of Open Access Journals (Sweden)

David Peón

2017-07-01

Full Text Available This paper overviews the theoretical and empirical research on behavioral biases and their influence in the literature. To provide a systematic exposition, we present a unified framework that takes the reader through an original taxonomy, based on the reviews of relevant authors in the field. In particular, we establish three broad categories that may be distinguished: heuristics and biases; choices, values and frames; and social factors. We then describe the main biases within each category, and revise the main theoretical and empirical developments, linking each bias with other biases and anomalies that are related to them, according to the literature.

Removing the interview for medical school selection is associated with gender bias among enrolled students.

Science.gov (United States)

Wilkinson, David; Casey, Mavourneen G; Eley, Diann S

2014-02-03

To report, and determine reasons for, a change in the gender ratio observed among enrolled medical students after removal of the interview from the selection process. Cross-sectional study of 4051 students admitted to the medical program at the University of Queensland between 2004 and 2012. Students are enrolled either directly as graduates or via a school-leaver pathway. Change in proportions of male and female students over time, and gender-specific scores in the three sections of the GAMSAT (Graduate Medical School Admissions Test). Between 2004 and 2008 (when an interview was part of the selection process), 891 enrolled students (51.4%) were male, whereas between 2009 and 2012 (no interview), 1134 (57.7%; P interview was removed to 64.0% (514 students; P interview (reaching 73.8% in 2012). Between 2004 and 2012, male students consistently performed better than female students on GAMSAT section III (mean score, 71.5 v 68.5; P interview from the selection process. This change is limited to domestic direct graduate-entry students, and seems to be due to higher scores by male students in section III of the GAMSAT. The interview may play an important role in ensuring gender equity in selection, and medical schools should carefully monitor the consequences of changes to selection policy.

Probing Biased Signaling in Chemokine Receptors

DEFF Research Database (Denmark)

Amarandi, Roxana Maria; Hjortø, Gertrud Malene; Rosenkilde, Mette Marie

2016-01-01

The chemokine system mediates leukocyte migration during homeostatic and inflammatory processes. Traditionally, it is described as redundant and promiscuous, with a single chemokine ligand binding to different receptors and a single receptor having several ligands. Signaling of chemokine receptors...... of others has been termed signaling bias and can accordingly be grouped into ligand bias, receptor bias, and tissue bias. Bias has so far been broadly overlooked in the process of drug development. The low number of currently approved drugs targeting the chemokine system, as well as the broad range...... of failed clinical trials, reflects the need for a better understanding of the chemokine system. Thus, understanding the character, direction, and consequence of biased signaling in the chemokine system may aid the development of new therapeutics. This review describes experiments to assess G protein...

Per-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling: A case study in environmental remote sensing

Science.gov (United States)

Gao, Jing; Burt, James E.

2017-12-01

This study investigates the usefulness of a per-pixel bias-variance error decomposition (BVD) for understanding and improving spatially-explicit data-driven models of continuous variables in environmental remote sensing (ERS). BVD is a model evaluation method originated from machine learning and have not been examined for ERS applications. Demonstrated with a showcase regression tree model mapping land imperviousness (0-100%) using Landsat images, our results showed that BVD can reveal sources of estimation errors, map how these sources vary across space, reveal the effects of various model characteristics on estimation accuracy, and enable in-depth comparison of different error metrics. Specifically, BVD bias maps can help analysts identify and delineate model spatial non-stationarity; BVD variance maps can indicate potential effects of ensemble methods (e.g. bagging), and inform efficient training sample allocation - training samples should capture the full complexity of the modeled process, and more samples should be allocated to regions with more complex underlying processes rather than regions covering larger areas. Through examining the relationships between model characteristics and their effects on estimation accuracy revealed by BVD for both absolute and squared errors (i.e. error is the absolute or the squared value of the difference between observation and estimate), we found that the two error metrics embody different diagnostic emphases, can lead to different conclusions about the same model, and may suggest different solutions for performance improvement. We emphasize BVD's strength in revealing the connection between model characteristics and estimation accuracy, as understanding this relationship empowers analysts to effectively steer performance through model adjustments.

B1 mapping for bias-correction in quantitative T1 imaging of the brain at 3T using standard pulse sequences.

Science.gov (United States)

Boudreau, Mathieu; Tardif, Christine L; Stikov, Nikola; Sled, John G; Lee, Wayne; Pike, G Bruce

2017-12-01

B 1 mapping is important for many quantitative imaging protocols, particularly those that include whole-brain T 1 mapping using the variable flip angle (VFA) technique. However, B 1 mapping sequences are not typically available on many magnetic resonance imaging (MRI) scanners. The aim of this work was to demonstrate that B 1 mapping implemented using standard scanner product pulse sequences can produce B 1 (and VFA T 1 ) maps comparable in quality and acquisition time to advanced techniques. Six healthy subjects were scanned at 3.0T. An interleaved multislice spin-echo echo planar imaging double-angle (EPI-DA) B 1 mapping protocol, using a standard product pulse sequence, was compared to two alternative methods (actual flip angle imaging, AFI, and Bloch-Siegert shift, BS). Single-slice spin-echo DA B 1 maps were used as a reference for comparison (Ref. DA). VFA flip angles were scaled using each B 1 map prior to fitting T 1 ; the nominal flip angle case was also compared. The pooled-subject voxelwise correlation (ρ) for B 1 maps (BS/AFI/EPI-DA) relative to the reference B 1 scan (Ref. DA) were ρ = 0.92/0.95/0.98. VFA T 1 correlations using these maps were ρ = 0.86/0.88/0.96, much better than without B 1 correction (ρ = 0.53). The relative error for each B 1 map (BS/AFI/EPI-DA/Nominal) had 95 th percentiles of 5/4/3/13%. Our findings show that B 1 mapping implemented using product pulse sequences can provide excellent quality B 1 (and VFA T 1 ) maps, comparable to other custom techniques. This fast whole-brain measurement (∼2 min) can serve as an excellent alternative for researchers without access to advanced B 1 pulse sequences. 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1673-1682. © 2017 International Society for Magnetic Resonance in Medicine.

Bias-field equalizer for bubble memories

Science.gov (United States)

Keefe, G. E.

1977-01-01

Magnetoresistive Perm-alloy sensor monitors bias field required to maintain bubble memory. Sensor provides error signal that, in turn, corrects magnitude of bias field. Error signal from sensor can be used to control magnitude of bias field in either auxiliary set of bias-field coils around permanent magnet field, or current in small coils used to remagnetize permanent magnet by infrequent, short, high-current pulse or short sequence of pulses.

Struvite pyrolysate recycling combined with dry pyrolysis for ammonium removal from wastewater.

Science.gov (United States)

Yu, Rongtai; Geng, Jinju; Ren, Hongqiang; Wang, Yanru; Xu, Ke

2013-03-01

The dry pyrolysis of magnesium ammonium phosphate (MAP) with NaOH powder for ammonium release was investigated, as well as the utility of MAP pyrolysate recycling. The identities of the MAP pyrolysate and its derivatives were experimentally validated. The results showed that the pyrolysate was amorphous magnesium hydrogen phosphate (MgHPO4) and magnesium pyrophosphate (Mg2P2O7). The best molar ratio of sodium hydroxide (NaOH) powder to ammonium was 1:1, at 110°C for 3h. The optimum pH for pyrolysate recycling was 9.5. The ammonia removal ratio could be maintained above 80% with MAP pyrolysate recycling. Seed crystal inoculation increased the rate of MAP crystallization by 20.86%, as well as the MAP grain size (2.08nm with seeding versus 1.72nm without). MAP particle size with NaOH treatment decreased: d(0.5)=19.34μm versus d(0.5)=30.35μm for direct pyrolysis. The results demonstrated that crystal growth was controlled by adding NaOH during MAP pyrolysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

A regularized, model-based approach to phase-based conductivity mapping using MRI.

Science.gov (United States)

Ropella, Kathleen M; Noll, Douglas C

2017-11-01

To develop a novel regularized, model-based approach to phase-based conductivity mapping that uses structural information to improve the accuracy of conductivity maps. The inverse of the three-dimensional Laplacian operator is used to model the relationship between measured phase maps and the object conductivity in a penalized weighted least-squares optimization problem. Spatial masks based on structural information are incorporated into the problem to preserve data near boundaries. The proposed Inverse Laplacian method was compared against a restricted Gaussian filter in simulation, phantom, and human experiments. The Inverse Laplacian method resulted in lower reconstruction bias and error due to noise in simulations than the Gaussian filter. The Inverse Laplacian method also produced conductivity maps closer to the measured values in a phantom and with reduced noise in the human brain, as compared to the Gaussian filter. The Inverse Laplacian method calculates conductivity maps with less noise and more accurate values near boundaries. Improving the accuracy of conductivity maps is integral for advancing the applications of conductivity mapping. Magn Reson Med 78:2011-2021, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Introduction to Unconscious Bias

Science.gov (United States)

Schmelz, Joan T.

2010-05-01

We all have biases, and we are (for the most part) unaware of them. In general, men and women BOTH unconsciously devalue the contributions of women. This can have a detrimental effect on grant proposals, job applications, and performance reviews. Sociology is way ahead of astronomy in these studies. When evaluating identical application packages, male and female University psychology professors preferred 2:1 to hire "Brian” over "Karen” as an assistant professor. When evaluating a more experienced record (at the point of promotion to tenure), reservations were expressed four times more often when the name was female. This unconscious bias has a repeated negative effect on Karen's career. This talk will introduce the concept of unconscious bias and also give recommendations on how to address it using an example for a faculty search committee. The process of eliminating unconscious bias begins with awareness, then moves to policy and practice, and ends with accountability.

Sensory experience modifies feature map relationships in visual cortex

Science.gov (United States)

Cloherty, Shaun L; Hughes, Nicholas J; Hietanen, Markus A; Bhagavatula, Partha S

2016-01-01

The extent to which brain structure is influenced by sensory input during development is a critical but controversial question. A paradigmatic system for studying this is the mammalian visual cortex. Maps of orientation preference (OP) and ocular dominance (OD) in the primary visual cortex of ferrets, cats and monkeys can be individually changed by altered visual input. However, the spatial relationship between OP and OD maps has appeared immutable. Using a computational model we predicted that biasing the visual input to orthogonal orientation in the two eyes should cause a shift of OP pinwheels towards the border of OD columns. We then confirmed this prediction by rearing cats wearing orthogonally oriented cylindrical lenses over each eye. Thus, the spatial relationship between OP and OD maps can be modified by visual experience, revealing a previously unknown degree of brain plasticity in response to sensory input. DOI: http://dx.doi.org/10.7554/eLife.13911.001 PMID:27310531

Research bias in judgement bias studies : a systematic review of valuation judgement literature

NARCIS (Netherlands)

Vincent Gruis; Pim Klamer; Cok Bakker

2017-01-01

Valuation judgement bias has been a research topic for several years due to its proclaimed effect on valuation accuracy. However, little is known on the emphasis of literature on judgement bias, with regard to, for instance, research methodologies, research context and robustness of research

Research bias in judgement bias studies : A systematic review of valuation judgement literature

NARCIS (Netherlands)

Klamer, Pim; Bakker, C.; Gruis, Vincent

2017-01-01

Valuation judgement bias has been a research topic for several years due to its proclaimed effect on valuation accuracy. However, little is known on the emphasis of literature on judgement bias, with regard to, for instance, research methodologies, research context and robustness of research

Attention bias modification training under working memory load increases the magnitude of change in attentional bias.

Science.gov (United States)

Clarke, Patrick J F; Branson, Sonya; Chen, Nigel T M; Van Bockstaele, Bram; Salemink, Elske; MacLeod, Colin; Notebaert, Lies

2017-12-01

Attention bias modification (ABM) procedures have shown promise as a therapeutic intervention, however current ABM procedures have proven inconsistent in their ability to reliably achieve the requisite change in attentional bias needed to produce emotional benefits. This highlights the need to better understand the precise task conditions that facilitate the intended change in attention bias in order to realise the therapeutic potential of ABM procedures. Based on the observation that change in attentional bias occurs largely outside conscious awareness, the aim of the current study was to determine if an ABM procedure delivered under conditions likely to preclude explicit awareness of the experimental contingency, via the addition of a working memory load, would contribute to greater change in attentional bias. Bias change was assessed among 122 participants in response to one of four ABM tasks given by the two experimental factors of ABM training procedure delivered either with or without working memory load, and training direction of either attend-negative or avoid-negative. Findings revealed that avoid-negative ABM procedure under working memory load resulted in significantly greater reductions in attentional bias compared to the equivalent no-load condition. The current findings will require replication with clinical samples to determine the utility of the current task for achieving emotional benefits. These present findings are consistent with the position that the addition of a working memory load may facilitate change in attentional bias in response to an ABM training procedure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Attribution bias and social anxiety in schizophrenia

Directory of Open Access Journals (Sweden)

Amelie M. Achim

2016-06-01

Full Text Available Studies on attribution biases in schizophrenia have produced mixed results, whereas such biases have been more consistently reported in people with anxiety disorders. Anxiety comorbidities are frequent in schizophrenia, in particular social anxiety disorder, which could influence their patterns of attribution biases. The objective of the present study was thus to determine if individuals with schizophrenia and a comorbid social anxiety disorder (SZ+ show distinct attribution biases as compared with individuals with schizophrenia without social anxiety (SZ− and healthy controls. Attribution biases were assessed with the Internal, Personal, and Situational Attributions Questionnaire in 41 individual with schizophrenia and 41 healthy controls. Results revealed the lack of the normal externalizing bias in SZ+, whereas SZ− did not significantly differ from healthy controls on this dimension. The personalizing bias was not influenced by social anxiety but was in contrast linked with delusions, with a greater personalizing bias in individuals with current delusions. Future studies on attribution biases in schizophrenia should carefully document symptom presentation, including social anxiety.

The effect of pylorus removal on delayed gastric emptying after pancreaticoduodenectomy: a meta-analysis of 2,599 patients.

Directory of Open Access Journals (Sweden)

Wenming Wu

Full Text Available BACKGROUND: Delayed gastric emptying is a serious complication of pancreaticoduodenectomy. The effect of pylorus removal on delayed gastric emptying has not been well evaluated. STUDY DESIGN: We searched five databases (PubMed, EMBASE and the Cochrane Central Register of Controlled Trials, Scopus and Web of Science up to July 2014. The meta-regression analysis was performed to evaluate any factors accountable for the heterogeneity. Publication bias was assessed by Egger's test, and corrected by Duval's trim and fill method. Subgroup analyses were conducted for different surgical techniques of pyloric removal. Other intraoperative and postoperative parameters were compared between two groups. RESULTS: We included 27 studies involving 2,599 patients, with a moderate-high heterogeneity for primary outcome (I(2 = 63%. Meta-regression analysis showed that four variables primarily contributed to the heterogeneity, namely nasogastric tube intubation time, solid food start time, preoperative diabetes percentage and the number of patients in pylorus-preserving group. After excluding four studies, the remaining twenty-three studies showed reduced heterogeneity (I(2 = 51%. Then we used Duval's trim and fill method to correct publication bias. The corrected MH odds ratio was 0.78 (95% CI: 0.52-1.17. A subgroup analysis showed that pylorus removal tends to reduce delayed gastric emptying incidence for subtotal stomach-preserving pancreaticoduodenectomy or pylorus-resecting pancreaticoduodenectomy, compared with pylorus-preserving group. However, standard Whipple procedure failed to show any significant reduction of DGE compared with pylorus-removal group. No significant differences were observed in terms of length of hospital stay, infection and pancreatic fistula; however, pylorus removal resulted in longer operation time, more blood loss and higher mortality. CONCLUSION: The pylorus removal does not significantly reduce the overall incidence of delayed

The fabrication of ordered arrays of exchange biased Ni/FeF2 nanostructures

International Nuclear Information System (INIS)

Kovylina, M; Labarta, A; Batlle, X; Erekhinsky, M; Schuller, I K; Morales, R

2010-01-01

The fabrication of ordered arrays of exchange biased Ni/FeF 2 nanostructures by focused ion beam lithography is reported. High quality nano-elements, with controlled removal depth and no significant re-deposition, were carved using small ion beam currents (30 pA), moderate dwell times (1 μs) and repeated passages over the same area. Two types of nanostructures were fabricated: square arrays of circular dots with diameters from 125 ± 8 to 500 ± 12 nm and periodicities ranging from 200 ± 8 to 1000 ± 12 nm, and square arrays of square antidots (207 ± 8 nm in edge length) with periodicities ranging from 300 ± 8 to 1200 ± 12 nm. The arrays were characterized using scanning ion and electron microscopy, and atomic force microscopy. The effect of the patterning on the exchange bias field (i.e., the shift in the hysteresis loop of ferromagnetic Ni due to proximity to antiferromagnetic FeF 2 ) was studied using magneto-transport measurements. These high quality nanostructures offer a unique method to address some of the open questions regarding the microscopic origin of exchange bias. This is not only of major relevance in the fabrication and miniaturization of magnetic devices but it is also one of the important proximity phenomena in nanoscience and materials science.

Time-efficient, high-resolution, whole brain three-dimensional macromolecular proton fraction mapping.

Science.gov (United States)

Yarnykh, Vasily L

2016-05-01

Macromolecular proton fraction (MPF) mapping is a quantitative MRI method that reconstructs parametric maps of a relative amount of macromolecular protons causing the magnetization transfer (MT) effect and provides a biomarker of myelination in neural tissues. This study aimed to develop a high-resolution whole brain MPF mapping technique using a minimal number of source images for scan time reduction. The described technique was based on replacement of an actually acquired reference image without MT saturation by a synthetic one reconstructed from R1 and proton density maps, thus requiring only three source images. This approach enabled whole brain three-dimensional MPF mapping with isotropic 1.25 × 1.25 × 1.25 mm(3) voxel size and a scan time of 20 min. The synthetic reference method was validated against standard MPF mapping with acquired reference images based on data from eight healthy subjects. Mean MPF values in segmented white and gray matter appeared in close agreement with no significant bias and small within-subject coefficients of variation (maps demonstrated sharp white-gray matter contrast and clear visualization of anatomical details, including gray matter structures with high iron content. The proposed synthetic reference method improves resolution of MPF mapping and combines accurate MPF measurements with unique neuroanatomical contrast features. © 2015 Wiley Periodicals, Inc.

Performance quantification of clustering algorithms for false positive removal in fMRI by ROC curves

Directory of Open Access Journals (Sweden)

André Salles Cunha Peres

Full Text Available Abstract Introduction Functional magnetic resonance imaging (fMRI is a non-invasive technique that allows the detection of specific cerebral functions in humans based on hemodynamic changes. The contrast changes are about 5%, making visual inspection impossible. Thus, statistic strategies are applied to infer which brain region is engaged in a task. However, the traditional methods like general linear model and cross-correlation utilize voxel-wise calculation, introducing a lot of false-positive data. So, in this work we tested post-processing cluster algorithms to diminish the false-positives. Methods In this study, three clustering algorithms (the hierarchical cluster, k-means and self-organizing maps were tested and compared for false-positive removal in the post-processing of cross-correlation analyses. Results Our results showed that the hierarchical cluster presented the best performance to remove the false positives in fMRI, being 2.3 times more accurate than k-means, and 1.9 times more accurate than self-organizing maps. Conclusion The hierarchical cluster presented the best performance in false-positive removal because it uses the inconsistency coefficient threshold, while k-means and self-organizing maps utilize a priori cluster number (centroids and neurons number; thus, the hierarchical cluster avoids clustering scattered voxels, as the inconsistency coefficient threshold allows only the voxels to be clustered that are at a minimum distance to some cluster.

INVESTIGATION OF 'HOT-SPOTS' AS A FUNCTION OF MATERIAL REMOVAL IN A LARGE-GRAIN NIOBIUM CAVITY

International Nuclear Information System (INIS)

Gianluigi Ciovati; Peter Kneisel

2006-01-01

Poster - The performance of a single-cell cavity made of RRR > 200 large-grain niobium has been investigated as a function of material removal by buffered chemical polishing. Temperature maps of the cavity surface at 1.7 and 2.0 K were taken for each step of chemical etching and revealed several 'hot-spots', which contribute to the degradation of the cavity quality factor as a function of the RF surface field, mostly at high field levels. It was found that the number of 'hot-spots' decreased for larger material removal. Interestingly, the losses of the 'hot-spots' at different locations evolved differently for successive material removal. The cavity achieved peak surface magnetic fields of about of 130 mT and was limited mostly by thermal quench. By measuring the temperature dependence of the surface resistance at low field between 4.2 K and 1.7 K, the variation of niobium material parameters as a function of material removal could also be investigated. This contribution shows the results of the RF tests along with the temperature maps and the analysis of the losses caused by the 'hot-spots'.

Biased Brownian dynamics for rate constant calculation.

OpenAIRE

Zou, G; Skeel, R D; Subramaniam, S

2000-01-01

An enhanced sampling method-biased Brownian dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampl...

SAT-MAP-CLIMATE project results[SATellite base bio-geophysical parameter MAPping and aggregation modelling for CLIMATE models

Energy Technology Data Exchange (ETDEWEB)

Bay Hasager, C.; Woetmann Nielsen, N.; Soegaard, H.; Boegh, E.; Hesselbjerg Christensen, J.; Jensen, N.O.; Schultz Rasmussen, M.; Astrup, P.; Dellwik, E.

2002-08-01

Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI). The observed parameters are used in the DMI-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronounced land-sea breeze effect which is also observable in field observations. The albedo maps from NOAA AVHRR are rather similar to the climatological mean values so for the HIRLAM model this is insignicant, yet most likely of some importance in the HIRHAM regional climate model. Land cover type maps are assigned local roughness values determined from meteorological field observations. Only maps with a spatial resolution around 25 m can adequately map the roughness variations of the typical patch size distribution in Denmark. A roughness map covering Denmark is aggregated (ie area-average non-linearly) by a microscale aggregation model that takes the non-linear turbulent responses of each roughness step change between patches in an arbitrary pattern into account. The effective roughnesses are calculated into a 15 km by 15 km grid for the HIRLAM model. The effect of hedgerows is included as an added roughness effect as a function of hedge density mapped from a digital vector map. Introducing the new effective roughness maps into the HIRLAM model appears to remedy on the seasonal wind speed bias over land and sea in spring. A new parameterisation on the effective roughness for scalar surface fluxes is developed and tested on synthetic data. Further is a method for the estimation the evapotranspiration from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of

The human hippocampus: cognitive maps or relational memory?

Science.gov (United States)

Kumaran, Dharshan; Maguire, Eleanor A

2005-08-03

The hippocampus is widely accepted to play a pivotal role in memory. Two influential theories offer competing accounts of its fundamental operating mechanism. The cognitive map theory posits a special role in mapping large-scale space, whereas the relational theory argues it supports amodal relational processing. Here, we pit the two theories against each other using a novel paradigm in which the relational processing involved in navigating in a city was matched with similar navigational and relational processing demands in a nonspatial (social) domain. During functional magnetic resonance imaging, participants determined the optimal route either between friends' homes or between the friends themselves using social connections. Separate brain networks were engaged preferentially during the two tasks, with hippocampal activation driven only by spatial relational processing. We conclude that the human hippocampus appears to have a bias toward the processing of spatial relationships, in accordance with the cognitive map theory. Our results both advance our understanding of the nature of the hippocampal contribution to memory and provide insights into how social networks are instantiated at the neural level.

Assessing total nitrogen in surface-water samples--precision and bias of analytical and computational methods

Science.gov (United States)

Rus, David L.; Patton, Charles J.; Mueller, David K.; Crawford, Charles G.

2013-01-01

concentrations up to 750 mg/L (median of -4.4 percent). This lent support to the laboratory-experiment finding that some particulate nitrogen is sequestered during the digestion process, and demonstrated that negative TN-A bias was present in samples with very low suspended-sediment concentrations. At sediment concentrations above 750 mg/L, the negative TN-A bias became more likely and larger (median of -13.2 percent), suggesting a secondary mechanism of bias, such as reagent limitation. From a geospatial perspective, trends in TN-A bias were not explained by selected basin characteristics. Though variable, TN-K bias generally was positive in the synoptic-field study (median of 3.1 percent), probably as a result of the reduction of nitrate. Three alternative approaches for assessing TN in surface water were evaluated for their impacts on existing and future sampling programs. Replacing TN-A with TN-C would remove the bias from subsequent data, but this approach also would introduce discontinuity in historical records. Replacing TN-K with TN-C would lead to the removal of positive bias in TN-K in the presence of elevated nitrate. However, in addition to the issues that may arise from a discontinuity in the data record, this approach may not be applicable to regulatory programs that require the use of total Kjeldahl nitrogen for stream assessment. By adding TN-C to existing TN-A or TN-K analyses, historical-data continuity would be preserved and the transitional period could be used to minimize the impact of bias on data analyses. This approach, however, imposes the greatest burdens on field operations and in terms of analytical costs. The variation in these impacts on different sampling programs will challenge U.S. Geological Survey scientists attempting to establish uniform standards for TN sample collection and analytical determinations.

Mechanisms of attentional selection bias for threatening emotions of anger and disgust in individuals with high-trait anxiety.

Science.gov (United States)

Xia, Luyao; Cui, Lixia; Zhang, Qin; Dong, Xiaofei; Shi, Guangyuan

2018-03-07

There are still some controversies that attentional bias to negative emotions in individuals with high-trait anxiety (HTA), as compare with those with low-trait anxiety (LTA), occurs in the engagement or disengagement facet of attentional selectivity and whether this attentional bias is affected by negative emotional types. In this study, we explored the different attentional selectivity mechanisms for threatening emotions of anger and disgust between individuals with HTA and LTA using the variant attentional-probe paradigm. The results showed that under the engagement condition, the HTA group's attentional bias index of the anger mood was negative and was significantly less than the disgusting mood (positive) and that the P1 was smaller with angry faces as compared with neutral faces, which was separate from the results of the disgusted faces, having a significant difference with neutral faces on P1 component. In the LTA group, under the disengagement condition, the attentional bias index of the disgusting mood was significantly bigger than the attentional bias index of the anger mood. Moreover, the P1 of the disgusted faces was significantly bigger than the P1 of the angry faces. The topographical maps were also made to reveal the different neural underpinnings. The results suggested that there were different mechanisms of selective attentional bias for threatening emotions of anger and disgust in individuals with HTA. HTA individuals were characterized by facilitated attentional engagement with angry faces and impaired attentional engagement with disgusted faces. LTA individuals had different neural underpinnings and had impaired attentional disengagement with disgusted faces.

Bias Correction of Satellite Precipitation Products (SPPs) using a User-friendly Tool: A Step in Enhancing Technical Capacity

Science.gov (United States)

Rushi, B. R.; Ellenburg, W. L.; Adams, E. C.; Flores, A.; Limaye, A. S.; Valdés-Pineda, R.; Roy, T.; Valdés, J. B.; Mithieu, F.; Omondi, S.

2017-12-01

SERVIR, a joint NASA-USAID initiative, works to build capacity in Earth observation technologies in developing countries for improved environmental decision making in the arena of: weather and climate, water and disasters, food security and land use/land cover. SERVIR partners with leading regional organizations in Eastern and Southern Africa, Hindu Kush-Himalaya, Mekong region, and West Africa to achieve its objectives. SERVIR develops hydrological applications to address specific needs articulated by key stakeholders and daily rainfall estimates are a vital input for these applications. Satellite-derived rainfall is subjected to systemic biases which need to be corrected before it can be used for any hydrologic application such as real-time or seasonal forecasting. SERVIR and the SWAAT team at the University of Arizona, have co-developed an open-source and user friendly tool of rainfall bias correction approaches for SPPs. Bias correction tools were developed based on Linear Scaling and Quantile Mapping techniques. A set of SPPs, such as PERSIANN-CCS, TMPA-RT, and CMORPH, are bias corrected using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data which incorporates ground based precipitation observations. This bias correction tools also contains a component, which is included to improve monthly mean of CHIRPS using precipitation products of the Global Surface Summary of the Day (GSOD) database developed by the National Climatic Data Center (NCDC). This tool takes input from command-line which makes it user-friendly and applicable in any operating platform without prior programming skills. This presentation will focus on this bias-correction tool for SPPs, including application scenarios.

Visualization of dielectric constant-electric field-temperature phase maps for imprinted relaxor ferroelectric thin films

International Nuclear Information System (INIS)

Frederick, J. C.; Kim, T. H.; Maeng, W.; Brewer, A. A.; Podkaminer, J. P.; Saenrang, W.; Vaithyanathan, V.; Schlom, D. G.; Li, F.; Chen, L.-Q.; Trolier-McKinstry, S.; Rzchowski, M. S.; Eom, C. B.

2016-01-01

The dielectric phase transition behavior of imprinted lead magnesium niobate–lead titanate relaxor ferroelectric thin films was mapped as a function of temperature and dc bias. To compensate for the presence of internal fields, an external electric bias was applied while measuring dielectric responses. The constructed three-dimensional dielectric maps provide insight into the dielectric behaviors of relaxor ferroelectric films as well as the temperature stability of the imprint. The transition temperature and diffuseness of the dielectric response correlate with crystallographic disorder resulting from strain and defects in the films grown on strontium titanate and silicon substrates; the latter was shown to induce a greater degree of disorder in the film as well as a dielectric response lower in magnitude and more diffuse in nature over the same temperature region. Strong and stable imprint was exhibited in both films and can be utilized to enhance the operational stability of piezoelectric devices through domain self-poling.

The coalitional value theory of antigay bias

NARCIS (Netherlands)

Winegard, Bo; Reynolds, Tania; Baumeister, Roy F.; Plant, E. Ashby

2016-01-01

Research indicates that antigay bias follows a specific pattern (and probably has throughout written history, at least in the West): (a) men evince more antigay bias than women; (b) men who belong to traditionally male coalitions evince more antigay bias than those who do not; (c) antigay bias is

Symmetry as Bias: Rediscovering Special Relativity

Science.gov (United States)

Lowry, Michael R.

1992-01-01

This paper describes a rational reconstruction of Einstein's discovery of special relativity, validated through an implementation: the Erlanger program. Einstein's discovery of special relativity revolutionized both the content of physics and the research strategy used by theoretical physicists. This research strategy entails a mutual bootstrapping process between a hypothesis space for biases, defined through different postulated symmetries of the universe, and a hypothesis space for physical theories. The invariance principle mutually constrains these two spaces. The invariance principle enables detecting when an evolving physical theory becomes inconsistent with its bias, and also when the biases for theories describing different phenomena are inconsistent. Structural properties of the invariance principle facilitate generating a new bias when an inconsistency is detected. After a new bias is generated. this principle facilitates reformulating the old, inconsistent theory by treating the latter as a limiting approximation. The structural properties of the invariance principle can be suitably generalized to other types of biases to enable primal-dual learning.

Removal kinetics of organic compounds and sum parameters under field conditions for managed aquifer recharge.

Science.gov (United States)

Wiese, Bernd; Massmann, Gudrun; Jekel, Martin; Heberer, Thomas; Dünnbier, Uwe; Orlikowski, Dagmar; Grützmacher, Gesche

2011-10-15

Managed aquifer recharge (MAR) provides efficient removal for many organic compounds and sum parameters. However, observed in situ removal efficiencies tend to scatter and cannot be predicted easily. In this paper, a method is introduced which allows to identify and eliminate biased samples and to quantify simultaneously the impact of (i) redox conditions (ii) kinetics (iii) residual threshold values below which no removal occurs and (iv) field site specifics. It enables to rule out spurious correlations between these factors and therefore improves the predictive power. The method is applied to an extensive database from three MAR field sites which was compiled in the NASRI project (2002-2005, Berlin, Germany). Removal characteristics for 38 organic parameters are obtained, of which 9 are analysed independently in 2 different laboratories. Out of these parameters, mainly pharmaceutically active compounds (PhAC) but also sum parameters and industrial chemicals, four compounds are shown to be readily removable whereas six are persistent. All partly removable compounds show a redox dependency and most of them reveal either kinetic dependencies or residual threshold values, which are determined. Differing removal efficiencies at different field sites can usually be explained by characteristics (i) to (iii). Copyright © 2011 Elsevier Ltd. All rights reserved.

Anti-Bias Education: Reflections

Science.gov (United States)

Derman-Sparks, Louise

2011-01-01

It is 30 years since NAEYC published "Anti-Bias Curriculum Tools for Empowering Young Children" (Derman-Sparks & ABC Task Force, 1989). Since then, anti-bias education concepts have become part of the early childhood education (ECE) narrative in the United States and many other countries. It has brought a fresh way of thinking about…

Reducing neutron multiplicity counting bias for plutonium warhead authentication

Energy Technology Data Exchange (ETDEWEB)

Goettsche, Malte

2015-06-05

Confidence in future nuclear arms control agreements could be enhanced by direct verification of warheads. It would include warhead authentication. This is the assessment based on measurements whether a declaration that a specific item is a nuclear warhead is true. An information barrier can be used to protect sensitive information during measurements. It could for example show whether attributes such as a fissile mass exceeding a threshold are met without indicating detailed measurement results. Neutron multiplicity measurements would be able to assess a plutonium fissile mass attribute if it were possible to show that their bias is low. Plutonium measurements have been conducted with the He-3 based Passive Scrap Multiplicity Counter. The measurement data has been used as a reference to test the capacity of the Monte Carlo code MCNPX-PoliMi to simulate neutron multiplicity measurements. The simulation results with their uncertainties are in agreement with the experimental results. It is essential to use cross-sections which include neutron scattering with the detector's polyethylene molecular structure. Further MCNPX-PoliMi simulations have been conducted in order to study bias that occurs when measuring samples with large plutonium masses such as warheads. Simulation results of solid and hollow metal spheres up to 6000 g show that the masses are underpredicted by as much as 20%. The main source of this bias has been identified in the false assumption that the neutron multiplication does not depend on the position where a spontaneous fission event occurred. The multiplication refers to the total number of neutrons leaking a sample after a primary spontaneous fission event, taking induced fission into consideration. The correction of the analysis has been derived and implemented in a MATLAB code. It depends on four geometry-dependent correction coefficients. When the sample configuration is fully known, these can be exactly determined and remove this type of

STACCATO: a novel solution to supernova photometric classification with biased training sets

Science.gov (United States)

Revsbech, E. A.; Trotta, R.; van Dyk, D. A.

2018-01-01

We present a new solution to the problem of classifying Type Ia supernovae from their light curves alone given a spectroscopically confirmed but biased training set, circumventing the need to obtain an observationally expensive unbiased training set. We use Gaussian processes (GPs) to model the supernovae's (SN's) light curves, and demonstrate that the choice of covariance function has only a small influence on the GPs ability to accurately classify SNe. We extend and improve the approach of Richards et al. - a diffusion map combined with a random forest classifier - to deal specifically with the case of biased training sets. We propose a novel method called Synthetically Augmented Light Curve Classification (STACCATO) that synthetically augments a biased training set by generating additional training data from the fitted GPs. Key to the success of the method is the partitioning of the observations into subgroups based on their propensity score of being included in the training set. Using simulated light curve data, we show that STACCATO increases performance, as measured by the area under the Receiver Operating Characteristic curve (AUC), from 0.93 to 0.96, close to the AUC of 0.977 obtained using the 'gold standard' of an unbiased training set and significantly improving on the previous best result of 0.88. STACCATO also increases the true positive rate for SNIa classification by up to a factor of 50 for high-redshift/low-brightness SNe.

Unbiased contaminant removal for 3D galaxy power spectrum measurements

Science.gov (United States)

Kalus, B.; Percival, W. J.; Bacon, D. J.; Samushia, L.

2016-11-01

We assess and develop techniques to remove contaminants when calculating the 3D galaxy power spectrum. We separate the process into three separate stages: (I) removing the contaminant signal, (II) estimating the uncontaminated cosmological power spectrum and (III) debiasing the resulting estimates. For (I), we show that removing the best-fitting contaminant (mode subtraction) and setting the contaminated components of the covariance to be infinite (mode deprojection) are mathematically equivalent. For (II), performing a quadratic maximum likelihood (QML) estimate after mode deprojection gives an optimal unbiased solution, although it requires the manipulation of large N_mode^2 matrices (Nmode being the total number of modes), which is unfeasible for recent 3D galaxy surveys. Measuring a binned average of the modes for (II) as proposed by Feldman, Kaiser & Peacock (FKP) is faster and simpler, but is sub-optimal and gives rise to a biased solution. We present a method to debias the resulting FKP measurements that does not require any large matrix calculations. We argue that the sub-optimality of the FKP estimator compared with the QML estimator, caused by contaminants, is less severe than that commonly ignored due to the survey window.

Direct mapping of light propagation in photonic crystal waveguides

DEFF Research Database (Denmark)

Bozhevolnyi, S.I.; Volkov, V.S.; Arentoft, J.

2002-01-01

Using near-field optical microscopy, we directly map the propagation of light in the wavelength range of 1510-1560 nm along bent photonic crystal waveguides formed by removing a single row of holes in the triangular 400-nm-period lattice and connected to access ridge waveguides, the structure being...

Sampler bias -- Phase 1

International Nuclear Information System (INIS)

Blanchard, R.J.

1995-01-01

This documents Phase 1 determinations on sampler induced bias for four sampler types used in tank characterization. Each sampler, grab sampler or bottle-on-a-string, auger sampler, sludge sampler and universal sampler, is briefly discussed and their physical limits noted. Phase 2 of this document will define additional testing and analysis to further define Sampler Bias

Combination of struvite pyrolysate recycling with mixed-base technology for removing ammonium from fertilizer wastewater.

Science.gov (United States)

Yu, Rongtai; Geng, Jinju; Ren, Hongqiang; Wang, Yanru; Xu, Ke

2012-11-01

Removal of ammonium from wastewater via struvite (MAP) pyrolysate recycling combined with a mixed-base NaOH/Mg(OH)(2) technology was investigated, and the phosphate and magnesium concentration in the supernatant were measured. The optimal parameters for acidolysis were a pH of 1; temperature of 120°C and time of 2h. The presence of derivatives of amorphous magnesium hydrogen phosphate (MgHPO(4)), namely magnesium phosphate (Mg(3)(PO(4))(2)) and magnesium pyrophosphate (Mg(2)P(2)O(7)) were verified by experiment. The ammonium removal ratio in this combined mixed-base technology was 96.8% in the first cycle, 80.6% in the second, and 81.0% after acidolysis. The phosphate and magnesium ions concentration in the supernatant were about 1mg/L and 40 mg/L, respectively. The grain size of MAP was 1.52 nm without seeding and 1.79 nm with seeding, and the growth rate of MAP was 17.6%. Copyright © 2012 Elsevier Ltd. All rights reserved.

Negativity Bias in Dangerous Drivers.

Directory of Open Access Journals (Sweden)

Jing Chai

Full Text Available The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes.

Reinforcement function design and bias for efficient learning in mobile robots

International Nuclear Information System (INIS)

Touzet, C.; Santos, J.M.

1998-01-01

The main paradigm in sub-symbolic learning robot domain is the reinforcement learning method. Various techniques have been developed to deal with the memorization/generalization problem, demonstrating the superior ability of artificial neural network implementations. In this paper, the authors address the issue of designing the reinforcement so as to optimize the exploration part of the learning. They also present and summarize works relative to the use of bias intended to achieve the effective synthesis of the desired behavior. Demonstrative experiments involving a self-organizing map implementation of the Q-learning and real mobile robots (Nomad 200 and Khepera) in a task of obstacle avoidance behavior synthesis are described. 3 figs., 5 tabs

Religious Attitudes and Home Bias

OpenAIRE

C. Reggiani; G. Rossini

2008-01-01

Home bias affects trade in goods, services and financial assets. It is mostly generated by "natural" trade barriers. Among these dividers we may list many behavioral and sociological factors, such as status quo biases and a few kind of ‘embeddedness’. Unfortunately these factors are difficult to measure. An important part of ‘embeddedness’ may be related to religious attitudes. Is there any relation between economic home bias and religious attitudes at the individual tier? Our aim is to provi...

Mapping snakebite epidemiology in Nicaragua--pitfalls and possible solutions.

Directory of Open Access Journals (Sweden)

Erik Hansson

Full Text Available BACKGROUND: Snakebites are a public health problem in Nicaragua: it is a tropical developing country, venomous snakes are present and there are reports of snakebites treated both in the formal and informal health care system. We aimed to produce an incidence map using data reported by the health care system that would be used to allocate resources. However, this map may suffer from case detection bias and decisions based on this map will neglect snakebite victims who do not receive healthcare. To avoid this error, we try to identify where underreporting is likely based on available information. METHOD AND FINDINGS: The Nicaraguan municipalities are categorized by precipitation, altitude and geographical location into regions of assumed homogenous snake prevalence. Socio-economic and healthcare variables hypothesized to be related to underreporting of snakebites are aggregated into an index. The environmental region variable, the underreporting index and three demographic variables (rurality, sex and age distribution are entered in a Poisson regression model of municipality-level snakebite incidence. In this model, the underreporting index is non-linearly associated with snakebite incidence, a finding we attribute to underreporting in the most deprived municipalities. The municipalities with the worst scoring on the underreporting index and those with combined low reported incidence and large rural population are identified as likely underreporting. 3,286 snakebite cases were reported in 2005-2009, corresponding to a 5-year incidence of 56 bites per 100,000 inhabitants (municipality range: 0-600 cases per 100,000 inhabitants. CONCLUSIONS: Using publicly available data, we identified areas likely to be underreporting snakebites and highlighted these areas instead of leaving them "white" on the incidence map. The effects of the case detection bias on the distribution of resources against snakebites could decrease. Although not yet verified

Placebo effect studies are susceptible to response bias and to other types of biases

DEFF Research Database (Denmark)

Hróbjartsson, Asbjørn; Kaptchuk, Ted J; Miller, Franklin G

2011-01-01

Investigations of the effect of placebo are often challenging to conduct and interpret. The history of placebo shows that assessment of its clinical significance has a real potential to be biased. We analyze and discuss typical types of bias in studies on placebo....

A Comparison of attentional biases and memory biases in social phobia and major depression

NARCIS (Netherlands)

Rinck, M.; Becker, E.S.

2005-01-01

Cognitive processes play an important role in the etiology and maintenance of anxiety and depression. Current theories differ, however, in their predictions regarding the occurrence of attentional biases and memory biases in depression and anxiety. To allow for a systematic comparison of disorders

Imprint of non-linear effects on HI intensity mapping on large scales

Energy Technology Data Exchange (ETDEWEB)

Umeh, Obinna, E-mail: umeobinna@gmail.com [Department of Physics and Astronomy, University of the Western Cape, Cape Town 7535 (South Africa)

2017-06-01

Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result and the renormalization prescription for biased tracers to study the impact of nonlinear effects on the power spectrum of HI brightness temperature both in real and redshift space. We show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortion terms modulate the power spectrum on large scales. The large scale modulation may be understood to be due to the effective bias parameter and effective shot noise.

Are most samples of animals systematically biased? Consistent individual trait differences bias samples despite random sampling.

Science.gov (United States)

Biro, Peter A

2013-02-01

Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.

EnviroAtlas - Crop phosphorus removal by 12-digit HUC for 2012 for the Conterminous United States

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas national map displays the mean crop phosphorus (P) removal from croplands in the conterminous United States (excluding Hawaii and Alaska) for the...

Scale-up of the electrokinetic fence technology for the removal of pesticides. Part II: Does size matter for removal of herbicides?

Science.gov (United States)

López-Vizcaíno, R; Risco, C; Isidro, J; Rodrigo, S; Saez, C; Cañizares, P; Navarro, V; Rodrigo, M A

2017-01-01

This work reports results of the application of electrokinetic fence technology in a 32 m 3 -prototype which contains soil polluted with 2,4-D and oxyfluorfen, focusing on the evaluation of the mechanisms that describe the removal of these two herbicides and comparing results to those obtained in smaller plants: a pilot-scale mockup (175 L) and a lab-scale soil column (1 L). Results show that electric heating of soil (coupled with the increase in the volatility) is the key to explain the removal of pollutants in the largest scale facility while electrokinetic transport processes are the primary mechanisms that explain the removal of herbicides in the lab-scale plant. 2-D and 3-D maps of the temperature and pollutant concentrations are used in the discussion of results trying to give light about the mechanisms and about how the size of the setup can lead to different conclusions, despite the same processes are occurring in the soil. Copyright © 2016 Elsevier Ltd. All rights reserved.

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework.

Directory of Open Access Journals (Sweden)

Qi Zheng

2016-10-01

Full Text Available Accurate mapping of next-generation sequencing (NGS reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost's algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost.

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework.

Science.gov (United States)

Zheng, Qi; Grice, Elizabeth A

2016-10-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost's algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost.

Adaptable history biases in human perceptual decisions.

Science.gov (United States)

Abrahamyan, Arman; Silva, Laura Luz; Dakin, Steven C; Carandini, Matteo; Gardner, Justin L

2016-06-21

When making choices under conditions of perceptual uncertainty, past experience can play a vital role. However, it can also lead to biases that worsen decisions. Consistent with previous observations, we found that human choices are influenced by the success or failure of past choices even in a standard two-alternative detection task, where choice history is irrelevant. The typical bias was one that made the subject switch choices after a failure. These choice history biases led to poorer performance and were similar for observers in different countries. They were well captured by a simple logistic regression model that had been previously applied to describe psychophysical performance in mice. Such irrational biases seem at odds with the principles of reinforcement learning, which would predict exquisite adaptability to choice history. We therefore asked whether subjects could adapt their irrational biases following changes in trial order statistics. Adaptability was strong in the direction that confirmed a subject's default biases, but weaker in the opposite direction, so that existing biases could not be eradicated. We conclude that humans can adapt choice history biases, but cannot easily overcome existing biases even if irrational in the current context: adaptation is more sensitive to confirmatory than contradictory statistics.

Domain wall engineering through exchange bias

International Nuclear Information System (INIS)

Albisetti, E.; Petti, D.

2016-01-01

The control of the structure and position of magnetic domain walls is at the basis of the development of different magnetic devices and architectures. Several nanofabrication techniques have been proposed to geometrically confine and shape domain wall structures; however, a fine tuning of the position and micromagnetic configuration is hardly achieved, especially in continuous films. This work shows that, by controlling the unidirectional anisotropy of a continuous ferromagnetic film through exchange bias, domain walls whose spin arrangement is generally not favored by dipolar and exchange interactions can be created. Micromagnetic simulations reveal that the domain wall width, position and profile can be tuned by establishing an abrupt change in the direction and magnitude of the exchange bias field set in the system. - Highlights: • Micromagnetic simulations study domain walls in exchange biased thin films. • Novel domain wall configurations can be stabilized via exchange bias. • Domain walls nucleate at the boundary of regions with different exchange bias. • Domain wall width and spin profile are controlled by tuning the exchange bias.

How we categorize objects is related to how we remember them: The shape bias as a memory bias.

Science.gov (United States)

Vlach, Haley A

2016-12-01

The "shape bias" describes the phenomenon that, after a certain point in development, children and adults generalize object categories based on shape to a greater degree than other perceptual features. The focus of research on the shape bias has been to examine the types of information that learners attend to in one moment in time. The current work takes a different approach by examining whether learners' categorical biases are related to their retention of information across time. In three experiments, children's (N=72) and adults' (N=240) memory performance for features of objects was examined in relation to their categorical biases. The results of these experiments demonstrated that the number of shape matches chosen during the shape bias task significantly predicted shape memory. Moreover, children and adults with a shape bias were more likely to remember the shape of objects than the color and size of objects. Taken together, this work suggests that the development of a shape bias may engender better memory for shape information. Copyright © 2016 Elsevier Inc. All rights reserved.

Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups.

Science.gov (United States)

Zwaan, Laura; Monteiro, Sandra; Sherbino, Jonathan; Ilgen, Jonathan; Howey, Betty; Norman, Geoffrey

2017-02-01

Many authors have implicated cognitive biases as a primary cause of diagnostic error. If this is so, then physicians already familiar with common cognitive biases should consistently identify biases present in a clinical workup. The aim of this paper is to determine whether physicians agree on the presence or absence of particular biases in a clinical case workup and how case outcome knowledge affects bias identification. We conducted a web survey of 37 physicians. Each participant read eight cases and listed which biases were present from a list provided. In half the cases the outcome implied a correct diagnosis; in the other half, it implied an incorrect diagnosis. We compared the number of biases identified when the outcome implied a correct or incorrect primary diagnosis. Additionally, the agreement among participants about presence or absence of specific biases was assessed. When the case outcome implied a correct diagnosis, an average of 1.75 cognitive biases were reported; when incorrect, 3.45 biases (F=71.3, p<0.00001). Individual biases were reported from 73% to 125% more often when an incorrect diagnosis was implied. There was no agreement on presence or absence of individual biases, with κ ranging from 0.000 to 0.044. Individual physicians are unable to agree on the presence or absence of individual cognitive biases. Their judgements are heavily influenced by hindsight bias; when the outcome implies a diagnostic error, twice as many biases are identified. The results present challenges for current error reduction strategies based on identification of cognitive biases. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Foreground removal from WMAP 7 yr polarization maps using an MLP neural network

DEFF Research Database (Denmark)

Nørgaard-Nielsen, Hans Ulrik

2012-01-01

. As a concrete example, the WMAP 7-year polarization data, the most reliable determination of the polarization properties of the CMB, has been analyzed. The analysis has adopted the frequency maps, noise models, window functions and the foreground models as provided by the WMAP Team, and no auxiliary data...

Correcting Biases in a lower resolution global circulation model with data assimilation

Science.gov (United States)

Canter, Martin; Barth, Alexander

2016-04-01

With this work, we aim at developping a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias. First, through a preliminary run, we estimate the bias of the model and its possible sources. Then, we establish a forcing term which is directly added inside the model's equations. We create an ensemble of runs and consider the forcing term as a control variable during the assimilation of observations. We then use this analysed forcing term to correct the bias of the model. Since the forcing is added inside the model, it acts as a source term, unlike external forcings such as wind. This procedure has been developed and successfully tested with a twin experiment on a Lorenz 95 model. It is currently being applied and tested on the sea ice ocean NEMO LIM model, which is used in the PredAntar project. NEMO LIM is a global and low resolution (2 degrees) coupled model (hydrodynamic model and sea ice model) with long time steps allowing simulations over several decades. Due to its low resolution, the model is subject to bias in area where strong currents are present. We aim at correcting this bias by using perturbed current fields from higher resolution models and randomly generated perturbations. The random perturbations need to be constrained in order to respect the physical properties of the ocean, and not create unwanted phenomena. To construct those random perturbations, we first create a random field with the Diva tool (Data-Interpolating Variational Analysis). Using a cost function, this tool penalizes abrupt variations in the field, while using a custom correlation length. It also decouples disconnected areas based on topography. Then, we filter the field to smoothen it and remove small scale variations. We use this field as a random stream function, and take its derivatives to get zonal and meridional velocity fields. We also constrain the stream function along the coasts in order not to have

AC bias operation of the perpendicular biased ferrite tuned cavity for the TRIUMF KAON Factory booster synchrotron

International Nuclear Information System (INIS)

Poirier, R.L.; Enegren, T.A.; Enchevich, I.B.

1991-05-01

The RF cavity for the booster synchrotron requires a frequency swing from 46 MHz at a repetition rate of 50 Hz and a maximum accelerating gap voltage of 65 kV. A DC biased prototype cavity built at LANL using perpendicular-biased yttrium-garnet ferrites, rather than the more conventional parallel-biased NiZn ferrites, has now undergone major reconstruction at TRIUMF for AC bias operation. RF signal level measurements have shown that the frequency swing at a repetition rate of 50 Hz can be accomplished and still handle the eddy current losses in the cavity structures with minimal effect on the magnetizing field. The prototype cavity is now undergoing high power RF tests with full power AC bias operation. The results of these tests and operational experience is reported. (Author) ref., 6 figs

delta-biased Josephson tunnel junctions

DEFF Research Database (Denmark)

Monaco, R.; Mygind, Jesper; Koshelet, V.

2010-01-01

Abstract: The behavior of a long Josephson tunnel junction drastically depends on the distribution of the dc bias current. We investigate the case in which the bias current is fed in the central point of a one-dimensional junction. Such junction configuration has been recently used to detect...... the persistent currents circulating in a superconducting loop. Analytical and numerical results indicate that the presence of fractional vortices leads to remarkable differences from the conventional case of uniformly distributed dc bias current. The theoretical findings are supported by detailed measurements...

Making maps of the cosmic microwave background: The MAXIMA example

Science.gov (United States)

Stompor, Radek; Balbi, Amedeo; Borrill, Julian D.; Ferreira, Pedro G.; Hanany, Shaul; Jaffe, Andrew H.; Lee, Adrian T.; Oh, Sang; Rabii, Bahman; Richards, Paul L.; Smoot, George F.; Winant, Celeste D.; Wu, Jiun-Huei Proty

2002-01-01

This work describes cosmic microwave background (CMB) data analysis algorithms and their implementations, developed to produce a pixelized map of the sky and a corresponding pixel-pixel noise correlation matrix from time ordered data for a CMB mapping experiment. We discuss in turn algorithms for estimating noise properties from the time ordered data, techniques for manipulating the time ordered data, and a number of variants of the maximum likelihood map-making procedure. We pay particular attention to issues pertinent to real CMB data, and present ways of incorporating them within the framework of maximum likelihood map making. Making a map of the sky is shown to be not only an intermediate step rendering an image of the sky, but also an important diagnostic stage, when tests for and/or removal of systematic effects can efficiently be performed. The case under study is the MAXIMA-I data set. However, the methods discussed are expected to be applicable to the analysis of other current and forthcoming CMB experiments.

The immitigable nature of assembly bias: the impact of halo definition on assembly bias

Science.gov (United States)

Villarreal, Antonio S.; Zentner, Andrew R.; Mao, Yao-Yuan; Purcell, Chris W.; van den Bosch, Frank C.; Diemer, Benedikt; Lange, Johannes U.; Wang, Kuan; Campbell, Duncan

2017-11-01

Dark matter halo clustering depends not only on halo mass, but also on other properties such as concentration and shape. This phenomenon is known broadly as assembly bias. We explore the dependence of assembly bias on halo definition, parametrized by spherical overdensity parameter, Δ. We summarize the strength of concentration-, shape-, and spin-dependent halo clustering as a function of halo mass and halo definition. Concentration-dependent clustering depends strongly on mass at all Δ. For conventional halo definitions (Δ ∼ 200 - 600 m), concentration-dependent clustering at low mass is driven by a population of haloes that is altered through interactions with neighbouring haloes. Concentration-dependent clustering can be greatly reduced through a mass-dependent halo definition with Δ ∼ 20 - 40 m for haloes with M200 m ≲ 1012 h-1M⊙. Smaller Δ implies larger radii and mitigates assembly bias at low mass by subsuming altered, so-called backsplash haloes into now larger host haloes. At higher masses (M200 m ≳ 1013 h-1M⊙) larger overdensities, Δ ≳ 600 m, are necessary. Shape- and spin-dependent clustering are significant for all halo definitions that we explore and exhibit a relatively weaker mass dependence. Generally, both the strength and the sense of assembly bias depend on halo definition, varying significantly even among common definitions. We identify no halo definition that mitigates all manifestations of assembly bias. A halo definition that mitigates assembly bias based on one halo property (e.g. concentration) must be mass dependent. The halo definitions that best mitigate concentration-dependent halo clustering do not coincide with the expected average splashback radii at fixed halo mass.

Is racial bias malleable? Whites' lay theories of racial bias predict divergent strategies for interracial interactions.

Science.gov (United States)

Neel, Rebecca; Shapiro, Jenessa R

2012-07-01

How do Whites approach interracial interactions? We argue that a previously unexamined factor-beliefs about the malleability of racial bias-guides Whites' strategies for difficult interracial interactions. We predicted and found that those who believe racial bias is malleable favor learning-oriented strategies such as taking the other person's perspective and trying to learn why an interaction is challenging, whereas those who believe racial bias is fixed favor performance-oriented strategies such as overcompensating in the interaction and trying to end the interaction as quickly as possible. Four studies support these predictions. Whether measured (Studies 1, 3, and 4) or manipulated (Study 2), beliefs that racial bias is fixed versus malleable yielded these divergent strategies for difficult interracial interactions. Furthermore, beliefs about the malleability of racial bias are distinct from related constructs (e.g., prejudice and motivations to respond without prejudice; Studies 1, 3, and 4) and influence self-reported (Studies 1-3) and actual (Study 4) strategies in imagined (Studies 1-2) and real (Studies 3-4) interracial interactions. Together, these findings demonstrate that beliefs about the malleability of racial bias influence Whites' approaches to and strategies within interracial interactions. PsycINFO Database Record (c) 2012 APA, all rights reserved

Bias correction for estimated QTL effects using the penalized maximum likelihood method.

Science.gov (United States)

Zhang, J; Yue, C; Zhang, Y-M

2012-04-01

A penalized maximum likelihood method has been proposed as an important approach to the detection of epistatic quantitative trait loci (QTL). However, this approach is not optimal in two special situations: (1) closely linked QTL with effects in opposite directions and (2) small-effect QTL, because the method produces downwardly biased estimates of QTL effects. The present study aims to correct the bias by using correction coefficients and shifting from the use of a uniform prior on the variance parameter of a QTL effect to that of a scaled inverse chi-square prior. The results of Monte Carlo simulation experiments show that the improved method increases the power from 25 to 88% in the detection of two closely linked QTL of equal size in opposite directions and from 60 to 80% in the identification of QTL with small effects (0.5% of the total phenotypic variance). We used the improved method to detect QTL responsible for the barley kernel weight trait using 145 doubled haploid lines developed in the North American Barley Genome Mapping Project. Application of the proposed method to other shrinkage estimation of QTL effects is discussed.

Attention bias to emotional information in children as a function of maternal emotional disorders and maternal attention biases.

Science.gov (United States)

Waters, Allison M; Forrest, Kylee; Peters, Rosie-Mae; Bradley, Brendan P; Mogg, Karin

2015-03-01

Children of parents with emotional disorders have an increased risk for developing anxiety and depressive disorders. Yet the mechanisms that contribute to this increased risk are poorly understood. The present study aimed to examine attention biases in children as a function of maternal lifetime emotional disorders and maternal attention biases. There were 134 participants, including 38 high-risk children, and their mothers who had lifetime emotional disorders; and 29 low-risk children, and their mothers without lifetime emotional disorders. Mothers and children completed a visual probe task with emotional face pairs presented for 500 ms. Attention bias in children did not significantly differ solely as a function of whether or not their mothers had lifetime emotional disorders. However, attention bias in high-risk children was significantly related to their mothers' attention bias. Specifically, children of mothers with lifetime emotional disorders showed a greater negative attention bias if their mothers had a greater tendency to direct attention away from positive information. This study was cross-sectional in nature, and therefore unable to assess long-term predictive effects. Also, just one exposure duration of 500 ms was utilised. Attention bias for negative information is greater in offspring of mothers who have lifetime emotional disorders and a reduced positive bias, which could be a risk marker for the development of emotional disorders in children.

Asymmetric neighborhood functions accelerate ordering process of self-organizing maps

International Nuclear Information System (INIS)

Ota, Kaiichiro; Aoki, Takaaki; Kurata, Koji; Aoyagi, Toshio

2011-01-01

A self-organizing map (SOM) algorithm can generate a topographic map from a high-dimensional stimulus space to a low-dimensional array of units. Because a topographic map preserves neighborhood relationships between the stimuli, the SOM can be applied to certain types of information processing such as data visualization. During the learning process, however, topological defects frequently emerge in the map. The presence of defects tends to drastically slow down the formation of a globally ordered topographic map. To remove such topological defects, it has been reported that an asymmetric neighborhood function is effective, but only in the simple case of mapping one-dimensional stimuli to a chain of units. In this paper, we demonstrate that even when high-dimensional stimuli are used, the asymmetric neighborhood function is effective for both artificial and real-world data. Our results suggest that applying the asymmetric neighborhood function to the SOM algorithm improves the reliability of the algorithm. In addition, it enables processing of complicated, high-dimensional data by using this algorithm.

Does neurocognitive function affect cognitive bias toward an emotional stimulus? Association between general attentional ability and attentional bias toward threat

Directory of Open Access Journals (Sweden)

Yuko eHakamata

2014-08-01

Full Text Available Background: Although poorer cognitive performance has been found to be associated with anxiety, it remains unclear whether neurocognitive function affects biased cognitive processing toward emotional information. We investigated whether general cognitive function evaluated with a standard neuropsychological test predicts biased cognition, focusing on attentional bias toward threat.Methods: One hundred and five healthy young adults completed a dot-probe task measuring attentional bias and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS measuring general cognitive function, which consists of five domains: immediate memory, visuospatial/constructional, language, attention, and delayed memory. Stepwise multiple regression analysis was performed to examine the relationships between attentional bias and cognitive function. Results: The attentional domain was the best predictor of attentional bias toward threat (β = -0.26, p = 0.006. Within the attentional domain, digit symbol coding was negatively correlated with attentional bias (r = -0.28, p = 0.005.Conclusions: The present study provides the first evidence that general attentional ability, which was assessed with a standard neuropsychological test, affects attentional bias toward threatening information. Individual cognitive profiles might be important for the measurement and modification of cognitive biases.

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Science.gov (United States)

Burgoon, Judee K.; Blair, J. Pete; Strom, Renee E.

2008-01-01

In potentially deceptive situations, people rely on mental shortcuts to help process information. These heuristic judgments are often biased and result in inaccurate assessments of sender veracity. Four such biases--truth bias, visual bias, demeanor bias, and expectancy violation bias--were examined in a judgment experiment that varied nonverbal…

The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

Science.gov (United States)

Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

2009-09-21

Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.

Methodology to develop maps of susceptibility to mass removal processes, case analysis south slope of Tuxtla Gutiérrez, Chiapas

Directory of Open Access Journals (Sweden)

J. A. Paz Tenorio

2017-03-01

classified as Very High Threat are the more susceptible to the occurrence of these events. It is to be expected that in time, the incidence of this type of phenomena is manifested in the levels of High and Very High Threat. Applying the Analytic Hierarchy Process (AHP developed by Saaty (1988, which consists of matrix analysis and involves value judgments. In this way the matrix of preference over the selected criteria was generated, obtaining the weighting of the five chosen variables. It was important the knowledge of the study area, the documentation and local studies generated to date, where the criteria of the specialists are taken up. The process was done in an Excel spreadsheet (2007 version, applying the corresponding formulas. Because only five variables and the size of the area (250 km2 were handled, no specialized software was required. With the data obtained a table was created in which a column with the name of "Threat" was created, which corresponds to the sum of the parameters of the six criteria mentioned above. This is reflected in the Map of Threats by Mass Removal Processes. Thus, in the one the extreme values are included in a range from 0 to 1. The map of hazard by removing processes in mass or landslide (PRM, was developed from the heuristic combination of multi-criteria analysis method, and determined five levels of threat in the urban area, covering the following percentages: Very Low 5%, Low 27.1%, Middle 39.3%, High 15.3% and Very High 13.3%, the latter being distributed mostly in slope deposits around La Mesa of Copoya, confirming their status as maximum hazard. For Tuxtla Gutierrez is estimated a population exposed about 62,500 inhabitants (11.6% of the total (537.102 inhabitants in the urban area who reside both in the southern part of the city and 30 rural towns settled on the flanks of La Mesa of Copoya; estimates about 28,000 dwellings exposed grouped into 850 blocks. Current trends in the growth of the city, make evident the need to manage

Does exclusion of protest zeros and warm-glow bidders cause selection bias in Contingent Valuation?

DEFF Research Database (Denmark)

Grammatikopoulou, Ioanna; Olsen, Søren Bøye; Pouta, Eija

A great issue of concern in valuation studies is whether respondents provide trustworthy and reliable answers conditional on the perceived information. Respondent may report either a higher than the true Willingness-To-Pay (WTP) due to warm glow or embedding effects or zero WTP which is lower than...... the true WTP due to protest behavior. We conduct a contingent valuation study to estimate the WTP for conserving a Natura 2000 wetland area in Greece. We find that 54% of the positive bidders exert warm glow motivations while 29% of all responses can be classified as protest zero bids. We employ three....... Our findings show that removal of warm glow positive bidders does not distort the WTP estimate in any significant way. However, using the same approach for protest zero bidders, we find strong evidence of selection bias associated with removal of protest zero responses. Specifically, WTP estimates...

Needlet estimation of cross-correlation between CMB lensing maps and LSS

Energy Technology Data Exchange (ETDEWEB)

Bianchini, Federico [Astrophysics Sector, SISSA, Via Bonomea 265, I-34136 Trieste (Italy); Renzi, Alessandro; Marinucci, Domenico, E-mail: fbianchini@sissa.it, E-mail: renzi@mat.uniroma2.it, E-mail: marinucc@mat.uniroma2.it [Dipartimento di Matematica, Università di Roma Tor Vergata, Via della Ricerca Scientifica 1, 00133 Roma (Italy)

2016-11-01

In this paper we develop a novel needlet-based estimator to investigate the cross-correlation between cosmic microwave background (CMB) lensing maps and large-scale structure (LSS) data. We compare this estimator with its harmonic counterpart and, in particular, we analyze the bias effects of different forms of masking. In order to address this bias, we also implement a MASTER-like technique in the needlet case. The resulting estimator turns out to have an extremely good signal-to-noise performance. Our analysis aims at expanding and optimizing the operating domains in CMB-LSS cross-correlation studies, similarly to CMB needlet data analysis. It is motivated especially by next generation experiments (such as Euclid) which will allow us to derive much tighter constraints on cosmological and astrophysical parameters through cross-correlation measurements between CMB and LSS.

Study of the Dependency on Magnetic Field and Bias Voltage of an AC-Biased TES Microcalorimeter

Science.gov (United States)

Gottardi, L.; Bruijn, M.; denHartog, R.; Hoevers, H.; deKorte, P.; vanderKuur, J.; Linderman, M.; Adams, J.; Bailey, C.; Bandler, S.;

Critical Thinking and Cognitive Bias

Directory of Open Access Journals (Sweden)

Jeffrey Maynes

2015-05-01

Full Text Available Teaching critical thinking skill is a central pedagogical aim in many courses. These skills, it is hoped, will be both portable (applicable in a wide range of contexts and durable (not forgotten quickly. Yet, both of these virtues are challenged by pervasive and potent cognitive biases, such as motivated reasoning, false consensus bias and hindsight bias. In this paper, I argue that a focus on the development of metacognitive skill shows promise as a means to inculcate debiasing habits in students. Such habits will help students become more critical reasoners. I close with suggestions for implementing this strategy.

Non-Gaussian halo assembly bias

International Nuclear Information System (INIS)

Reid, Beth A.; Verde, Licia; Dolag, Klaus; Matarrese, Sabino; Moscardini, Lauro

2010-01-01

The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f NL , offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the first detection of the dependence of the non-Gaussian halo bias on halo formation history using N-body simulations. We also present an analytic derivation of the expected signal based on the extended Press-Schechter formalism. In excellent agreement with our analytic prediction, we find that the halo formation history-dependent contribution to the non-Gaussian halo bias (which we call non-Gaussian halo assembly bias) can be factorized in a form approximately independent of redshift and halo mass. The correction to the non-Gaussian halo bias due to the halo formation history can be as large as 100%, with a suppression of the signal for recently formed halos and enhancement for old halos. This could in principle be a problem for realistic galaxy surveys if observational selection effects were to pick galaxies occupying only recently formed halos. Current semi-analytic galaxy formation models, for example, imply an enhancement in the expected signal of ∼ 23% and ∼ 48% for galaxies at z = 1 selected by stellar mass and star formation rate, respectively

Novel thermally stable poly(vinyl chloride) composites for sulfate removal

Energy Technology Data Exchange (ETDEWEB)

Nadagouda, Mallikarjuna N., E-mail: Nadagouda.mallikarjuna@epa.gov [Water Supply and Water Resources Division, National Risk Management Research Laboratory U.S. Environmental Protection Agency, 26 W. Martin Luther King Drive Cincinnati, Ohio 45268 (United States); Pressman, Jonathan; White, Colin; Speth, Thomas F.; McCurry, Daniel L. [Water Supply and Water Resources Division, National Risk Management Research Laboratory U.S. Environmental Protection Agency, 26 W. Martin Luther King Drive Cincinnati, Ohio 45268 (United States)

2011-04-15

Graphical abstract: Barium carbonate and/or barium carbonate-loaded silica aero-gels dispersed polyvinyl chloride (PVC) composites were prepared by dissolving PVC in tetrahydrofuran (THF), dispersing BaCO{sub 3} and/or BaCO{sub 3}-loaded silica aero-gels, re-precipitating the PVC with water at room temperature. The PVC composites were then characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray mapping, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The obtained composites had better thermal properties than the control PVC. The composites were tested for sulfate removal and found to significantly reduce sulfate when compared with control PVC. - Abstract: BaCO{sub 3} dispersed PVC composites were prepared through a polymer re-precipitation method. The composites were tested for sulfate removal using rapid small scale column test (RSSCT) and found to significantly reduce sulfate concentration. The method was extended to synthesize barium carbonate-loaded silica aero-gels-polyvinyl chloride (PVC) polymer composites. The PVC composites were characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray mapping, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The method has advantages over conventional sulfate precipitation (sulfate removal process) using BaCO{sub 3} wherein clogging of the filter can be avoided. The method is environmentally friendly and does not interfere with natural organic matter as the conventional resin does. Some of the composites were thermally more stable as compared with the pure PVC discussed in the literature.

Novel thermally stable poly(vinyl chloride) composites for sulfate removal

International Nuclear Information System (INIS)

Nadagouda, Mallikarjuna N.; Pressman, Jonathan; White, Colin; Speth, Thomas F.; McCurry, Daniel L.

2011-01-01

Graphical abstract: Barium carbonate and/or barium carbonate-loaded silica aero-gels dispersed polyvinyl chloride (PVC) composites were prepared by dissolving PVC in tetrahydrofuran (THF), dispersing BaCO 3 and/or BaCO 3 -loaded silica aero-gels, re-precipitating the PVC with water at room temperature. The PVC composites were then characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray mapping, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The obtained composites had better thermal properties than the control PVC. The composites were tested for sulfate removal and found to significantly reduce sulfate when compared with control PVC. - Abstract: BaCO 3 dispersed PVC composites were prepared through a polymer re-precipitation method. The composites were tested for sulfate removal using rapid small scale column test (RSSCT) and found to significantly reduce sulfate concentration. The method was extended to synthesize barium carbonate-loaded silica aero-gels-polyvinyl chloride (PVC) polymer composites. The PVC composites were characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray mapping, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The method has advantages over conventional sulfate precipitation (sulfate removal process) using BaCO 3 wherein clogging of the filter can be avoided. The method is environmentally friendly and does not interfere with natural organic matter as the conventional resin does. Some of the composites were thermally more stable as compared with the pure PVC discussed in the literature.

Attentional Bias towards Positive Emotion Predicts Stress Resilience.

Science.gov (United States)

Thoern, Hanna A; Grueschow, Marcus; Ehlert, Ulrike; Ruff, Christian C; Kleim, Birgit

2016-01-01

There is extensive evidence for an association between an attentional bias towards emotionally negative stimuli and vulnerability to stress-related psychopathology. Less is known about whether selective attention towards emotionally positive stimuli relates to mental health and stress resilience. The current study used a modified Dot Probe task to investigate if individual differences in attentional biases towards either happy or angry emotional stimuli, or an interaction between these biases, are related to self-reported trait stress resilience. In a nonclinical sample (N = 43), we indexed attentional biases as individual differences in reaction time for stimuli preceded by either happy or angry (compared to neutral) face stimuli. Participants with greater attentional bias towards happy faces (but not angry faces) reported higher trait resilience. However, an attentional bias towards angry stimuli moderated this effect: The attentional bias towards happy faces was only predictive for resilience in those individuals who also endorsed an attentional bias towards angry stimuli. An attentional bias towards positive emotional stimuli may thus be a protective factor contributing to stress resilience, specifically in those individuals who also endorse an attentional bias towards negative emotional stimuli. Our findings therefore suggest a novel target for prevention and treatment interventions addressing stress-related psychopathology.

Minimum Bias Trigger in ATLAS

International Nuclear Information System (INIS)

Kwee, Regina

2010-01-01

Since the restart of the LHC in November 2009, ATLAS has collected inelastic pp collisions to perform first measurements on charged particle densities. These measurements will help to constrain various models describing phenomenologically soft parton interactions. Understanding the trigger efficiencies for different event types are therefore crucial to minimize any possible bias in the event selection. ATLAS uses two main minimum bias triggers, featuring complementary detector components and trigger levels. While a hardware based first trigger level situated in the forward regions with 2.2 < |η| < 3.8 has been proven to select pp-collisions very efficiently, the Inner Detector based minimum bias trigger uses a random seed on filled bunches and central tracking detectors for the event selection. Both triggers were essential for the analysis of kinematic spectra of charged particles. Their performance and trigger efficiency measurements as well as studies on possible bias sources will be presented. We also highlight the advantage of these triggers for particle correlation analyses. (author)

Is there bias in editorial choice? Yes

OpenAIRE

Moustafa, Khaled

2018-01-01

Nature has recently published a Correspondence claiming the absence of fame biases in the editorial choice. The topic is interesting and deserves a deeper analysis than it was presented because the reported brief analysis and its conclusion are somewhat biased for many reasons, some of them are discussed here. Since the editorial assessment is a form of peer-review, the biases reported on external peer-reviews would, thus, apply to the editorial assessment, too. The biases would be proportion...

Improving real-time estimation of heavy-to-extreme precipitation using rain gauge data via conditional bias-penalized optimal estimation

Science.gov (United States)

Seo, Dong-Jun; Siddique, Ridwan; Zhang, Yu; Kim, Dongsoo

2014-11-01

A new technique for gauge-only precipitation analysis for improved estimation of heavy-to-extreme precipitation is described and evaluated. The technique is based on a novel extension of classical optimal linear estimation theory in which, in addition to error variance, Type-II conditional bias (CB) is explicitly minimized. When cast in the form of well-known kriging, the methodology yields a new kriging estimator, referred to as CB-penalized kriging (CBPK). CBPK, however, tends to yield negative estimates in areas of no or light precipitation. To address this, an extension of CBPK, referred to herein as extended conditional bias penalized kriging (ECBPK), has been developed which combines the CBPK estimate with a trivial estimate of zero precipitation. To evaluate ECBPK, we carried out real-world and synthetic experiments in which ECBPK and the gauge-only precipitation analysis procedure used in the NWS's Multisensor Precipitation Estimator (MPE) were compared for estimation of point precipitation and mean areal precipitation (MAP), respectively. The results indicate that ECBPK improves hourly gauge-only estimation of heavy-to-extreme precipitation significantly. The improvement is particularly large for estimation of MAP for a range of combinations of basin size and rain gauge network density. This paper describes the technique, summarizes the results and shares ideas for future research.

Australia's Bond Home Bias

OpenAIRE

Anil V. Mishra; Umaru B. Conteh

2014-01-01

This paper constructs the float adjusted measure of home bias and explores the determinants of bond home bias by employing the International Monetary Fund's high quality dataset (2001 to 2009) on cross-border bond investment. The paper finds that Australian investors' prefer investing in countries with higher economic development and more developed bond markets. Exchange rate volatility appears to be an impediment for cross-border bond investment. Investors prefer investing in countries with ...

Estimation and analysis of the short-term variations of multi-GNSS receiver differential code biases using global ionosphere maps

Science.gov (United States)

Li, Min; Yuan, Yunbin; Wang, Ningbo; Liu, Teng; Chen, Yongchang

2017-12-01

Care should be taken to minimize the adverse impact of differential code biases (DCBs) on global navigation satellite systems (GNSS)-derived ionospheric information determinations. For the sake of convenience, satellite and receiver DCB products provided by the International GNSS Service (IGS) are treated as constants over a period of 24 h (Li et al. (2014)). However, if DCB estimates show remarkable intra-day variability, the DCBs estimated as constants over 1-day period will partially account for ionospheric modeling error; in this case DCBs will be required to be estimated over shorter time period. Therefore, it is important to further gain insight into the short-term variation characteristics of receiver DCBs. In this contribution, the IGS combined global ionospheric maps and the German Aerospace Center (DLR)-provided satellite DCBs are used in the improved method to determine the multi-GNSS receiver DCBs with an hourly time resolution. The intra-day stability of the receiver DCBs is thereby analyzed in detail. Based on 1 month of data collected within the multi-GNSS experiment of the IGS, a good agreement within the receiver DCBs is found between the resulting receiver DCB estimates and multi-GNSS DCB products from the DLR at a level of 0.24 ns for GPS, 0.28 ns for GLONASS, 0.28 ns for BDS, and 0.30 ns for Galileo. Although most of the receiver DCBs are relatively stable over a 1-day period, large fluctuations (more than 9 ns between two consecutive hours) within the receiver DCBs can be found. We also demonstrate the impact of the significant short-term variations in receiver DCBs on the extraction of ionospheric total electron content (TEC), at a level of 12.96 TECu (TEC unit). Compared to daily receiver DCB estimates, the hourly DCB estimates obtained from this study can reflect the short-term variations of the DCB estimates more dedicatedly. The main conclusion is that preliminary analysis of characteristics of receiver DCB variations over short

A forward bias method for lag correction of an a-Si flat panel detector

International Nuclear Information System (INIS)

Starman, Jared; Tognina, Carlo; Partain, Larry; Fahrig, Rebecca

2012-01-01

Purpose: Digital a-Si flat panel (FP) x-ray detectors can exhibit detector lag, or residual signal, of several percent that can cause ghosting in projection images or severe shading artifacts, known as the radar artifact, in cone-beam computed tomography (CBCT) reconstructions. A major contributor to detector lag is believed to be defect states, or traps, in the a-Si layer of the FP. Software methods to characterize and correct for the detector lag exist, but they may make assumptions such as system linearity and time invariance, which may not be true. The purpose of this work is to investigate a new hardware based method to reduce lag in an a-Si FP and to evaluate its effectiveness at removing shading artifacts in CBCT reconstructions. The feasibility of a novel, partially hardware based solution is also examined. Methods: The proposed hardware solution for lag reduction requires only a minor change to the FP. For pulsed irradiation, the proposed method inserts a new operation step between the readout and data collection stages. During this new stage the photodiode is operated in a forward bias mode, which fills the defect states with charge. A Varian 4030CB panel was modified to allow for operation in the forward bias mode. The contrast of residual lag ghosts was measured for lag frames 2 and 100 after irradiation ceased for standard and forward bias modes. Detector step response, lag, SNR, modulation transfer function (MTF), and detective quantum efficiency (DQE) measurements were made with standard and forward bias firmware. CBCT data of pelvic and head phantoms were also collected. Results: Overall, the 2nd and 100th detector lag frame residual signals were reduced 70%-88% using the new method. SNR, MTF, and DQE measurements show a small decrease in collected signal and a small increase in noise. The forward bias hardware successfully reduced the radar artifact in the CBCT reconstruction of the pelvic and head phantoms by 48%-81%. Conclusions: Overall, the

A MAP Estimator for Simultaneous Superresolution and Detector Nonunifomity Correction

Directory of Open Access Journals (Sweden)

Douglas R. Droege

2007-01-01

Full Text Available During digital video acquisition, imagery may be degraded by a number of phenomena including undersampling, blur, and noise. Many systems, particularly those containing infrared focal plane array (FPA sensors, are also subject to detector nonuniformity. Nonuniformity, or fixed pattern noise, results from nonuniform responsivity of the photodetectors that make up the FPA. Here we propose a maximum a posteriori (MAP estimation framework for simultaneously addressing undersampling, linear blur, additive noise, and bias nonuniformity. In particular, we jointly estimate a superresolution (SR image and detector bias nonuniformity parameters from a sequence of observed frames. This algorithm can be applied to video in a variety of ways including using a moving temporal window of frames to process successive groups of frames. By combining SR and nonuniformity correction (NUC in this fashion, we demonstrate that superior results are possible compared with the more conventional approach of performing scene-based NUC followed by independent SR. The proposed MAP algorithm can be applied with or without SR, depending on the application and computational resources available. Even without SR, we believe that the proposed algorithm represents a novel and promising scene-based NUC technique. We present a number of experimental results to demonstrate the efficacy of the proposed algorithm. These include simulated imagery for quantitative analysis and real infrared video for qualitative analysis.

Systematic biases in human heading estimation.

Directory of Open Access Journals (Sweden)

Luigi F Cuturi

Full Text Available Heading estimation is vital to everyday navigation and locomotion. Despite extensive behavioral and physiological research on both visual and vestibular heading estimation over more than two decades, the accuracy of heading estimation has not yet been systematically evaluated. Therefore human visual and vestibular heading estimation was assessed in the horizontal plane using a motion platform and stereo visual display. Heading angle was overestimated during forward movements and underestimated during backward movements in response to both visual and vestibular stimuli, indicating an overall multimodal bias toward lateral directions. Lateral biases are consistent with the overrepresentation of lateral preferred directions observed in neural populations that carry visual and vestibular heading information, including MSTd and otolith afferent populations. Due to this overrepresentation, population vector decoding yields patterns of bias remarkably similar to those observed behaviorally. Lateral biases are inconsistent with standard bayesian accounts which predict that estimates should be biased toward the most common straight forward heading direction. Nevertheless, lateral biases may be functionally relevant. They effectively constitute a perceptual scale expansion around straight ahead which could allow for more precise estimation and provide a high gain feedback signal to facilitate maintenance of straight-forward heading during everyday navigation and locomotion.

The Accuracy Enhancing Effect of Biasing Cues

NARCIS (Netherlands)

W. Vanhouche (Wouter); S.M.J. van Osselaer (Stijn)

2009-01-01

textabstractExtrinsic cues such as price and irrelevant attributes have been shown to bias consumers’ product judgments. Results in this article replicate those findings in pretrial judgments but show that such biasing cues can improve quality judgments at a later point in time. Initially biasing

How we categorize objects is related to how we remember them: The shape bias as a memory bias

Science.gov (United States)

Vlach, Haley A.

2016-01-01

The “shape bias” describes the phenomenon that, after a certain point in development, children and adults generalize object categories based upon shape to a greater degree than other perceptual features. The focus of research on the shape bias has been to examine the types of information that learners attend to in one moment in time. The current work takes a different approach by examining whether learners' categorical biases are related to their retention of information across time. In three experiments, children's (N = 72) and adults' (N = 240) memory performance for features of objects was examined in relation to their categorical biases. The results of these experiments demonstrated that the number of shape matches chosen during the shape bias task significantly predicted shape memory. Moreover, children and adults with a shape bias were more likely to remember the shape of objects than they were the color and size of objects. Taken together, this work suggests the development of a shape bias may engender better memory for shape information. PMID:27454236

Positioning of Weight Bias: Moving towards Social Justice.

Science.gov (United States)

Nutter, Sarah; Russell-Mayhew, Shelly; Alberga, Angela S; Arthur, Nancy; Kassan, Anusha; Lund, Darren E; Sesma-Vazquez, Monica; Williams, Emily

2016-01-01

Weight bias is a form of stigma with detrimental effects on the health and wellness of individuals with large bodies. Researchers from various disciplines have recognized weight bias as an important topic for public health and for professional practice. To date, researchers from various areas have approached weight bias from independent perspectives and from differing theoretical orientations. In this paper, we examined the similarities and differences between three perspectives (i.e., weight-centric, non-weight-centric (health-centric), and health at every size) used to understand weight bias and approach weight bias research with regard to (a) language about people with large bodies, (b) theoretical position, (c) identified consequences of weight bias, and (d) identified influences on weight-based social inequity. We suggest that, despite differences, each perspective acknowledges the negative influences that position weight as being within individual control and the negative consequences of weight bias. We call for recognition and discussion of weight bias as a social justice issue in order to change the discourse and professional practices extended towards individuals with large bodies. We advocate for an emphasis on social justice as a uniting framework for interdisciplinary research on weight bias.

An inclusive taxonomy of behavioral biases

OpenAIRE

David Peón; Manel Antelo; Anxo Calvo-Silvosa

2017-01-01

This paper overviews the theoretical and empirical research on behavioral biases and their influence in the literature. To provide a systematic exposition, we present a unified framework that takes the reader through an original taxonomy, based on the reviews of relevant authors in the field. In particular, we establish three broad categories that may be distinguished: heuristics and biases; choices, values and frames; and social factors. We then describe the main biases within each category,...

Multi-contrast attenuation map synthesis for PET/MR scanners: assessment on FDG and Florbetapir PET tracers

Energy Technology Data Exchange (ETDEWEB)

Burgos, Ninon [University College London, Translational Imaging Group, Centre for Medical Image Computing, London (United Kingdom); Cardoso, M.J.; Modat, Marc; Ourselin, Sebastien [University College London, Translational Imaging Group, Centre for Medical Image Computing, London (United Kingdom); University College London, Dementia Research Centre, Institute of Neurology, London (United Kingdom); Thielemans, Kris; Dickson, John [University College London, Institute of Nuclear Medicine, London (United Kingdom); Schott, Jonathan M. [University College London, Dementia Research Centre, Institute of Neurology, London (United Kingdom); Atkinson, David [University College London, Centre for Medical Imaging, London (United Kingdom); Arridge, Simon R. [University College London, Centre for Medical Image Computing, London (United Kingdom); Hutton, Brian F. [University College London, Institute of Nuclear Medicine, London (United Kingdom); University of Wollongong, Centre for Medical Radiation Physics, Wollongong, NSW (Australia)

2015-08-15

Positron Emission Tomography/Magnetic Resonance Imaging (PET/MR) scanners are expected to offer a new range of clinical applications. Attenuation correction is an essential requirement for quantification of PET data but MRI images do not directly provide a patient-specific attenuation map. Methods We further validate and extend a Computed Tomography (CT) and attenuation map (μ-map) synthesis method based on pre-acquired MRI-CT image pairs. The validation consists of comparing the CT images synthesised with the proposed method to the original CT images. PET images were acquired using two different tracers ({sup 18}F-FDG and {sup 18}F-florbetapir). They were then reconstructed and corrected for attenuation using the synthetic μ-maps and compared to the reference PET images corrected with the CT-based μ-maps. During the validation, we observed that the CT synthesis was inaccurate in areas such as the neck and the cerebellum, and propose a refinement to mitigate these problems, as well as an extension of the method to multi-contrast MRI data. Results With the improvements proposed, a significant enhancement in CT synthesis, which results in a reduced absolute error and a decrease in the bias when reconstructing PET images, was observed. For both tracers, on average, the absolute difference between the reference PET images and the PET images corrected with the proposed method was less than 2%, with a bias inferior to 1%. Conclusion With the proposed method, attenuation information can be accurately derived from MRI images by synthesising CT using routine anatomical sequences. MRI sequences, or combination of sequences, can be used to synthesise CT images, as long as they provide sufficient anatomical information. (orig.)

Cognitive biases can affect moral intuitions about cognitive enhancement

Directory of Open Access Journals (Sweden)

Lucius eCaviola

2014-10-01

Full Text Available Research into cognitive biases that impair human judgment has mostly been applied to the area of economic decision-making. Ethical decision-making has been comparatively neglected. Since ethical decisions often involve very high individual as well as collective stakes, analyzing how cognitive biases affect them can be expected to yield important results. In this theoretical article, we consider the ethical debate about cognitive enhancement (CE and suggest a number of cognitive biases that are likely to affect moral intuitions and judgments about CE: status quo bias, loss aversion, risk aversion, omission bias, scope insensitivity, nature bias, and optimistic bias. We find that there are more well-documented biases that are likely to cause irrational aversion to CE than biases in the opposite direction. This suggests that common attitudes about CE are predominantly negatively biased. Within this new perspective, we hope that subsequent research will be able to elaborate this hypothesis and develop effective de-biasing techniques that can help increase the rationality of the public CE debate and thus improve our ethical decision-making.

Attentional biases toward body images in males at high risk of muscle dysmorphia

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Xinhong Jin

2018-01-01

Full Text Available Objective Although research on muscle dysmorphia (MD, a body dysmorphic disorder subtype, has recently increased, the causes and mechanisms underlying this disorder remain unclear. Results from studies examining disorders associated with body image suggest the involvement of self-schema in biasing attention toward specific body information. The present study examined whether individuals at higher risk of MD also display attentional biases toward specific types of body images. Methods The validated Chinese version of the Muscle Appearance Satisfaction Scale was used to distinguish men at higher and lower risk of MD. Sixty-five adult Chinese men at higher (HRMD, n = 33 and lower risk of MD (LRMD, n = 32 performed a visual probe task. Initially, an image of a bodybuilder with either larger or smaller musculature was presented on one side of a central point, with a neutral image of a car exterior presented on the other side along the horizontal plane for 2,000 ms. The paired images were removed, and a visual target (a dot was displayed in the location of one of the previously shown images. Participants were asked to indicate the location of the target, and their eye movements were recorded during the entire visual presentation. Participant reaction time and three eye movement measurements (gaze direction, first saccade latency, and first fixation duration were recorded for use in determining attentional bias. Results The HRMD group revealed biases in orienting and maintaining their attention on images of bodybuilders with larger musculatures. Participants in this group consequently had a shorter reaction time in identifying the target that appeared at the location in which an image of a bodybuilder with a larger musculature had been previously displayed. They also directed their initial gaze more frequently, had shorter saccade latency, and had longer first fixation duration on images of bodybuilders with larger musculatures (all p < .0001

Attentional biases toward body images in males at high risk of muscle dysmorphia.

Science.gov (United States)

Jin, Xinhong; Jin, Yahong; Zhou, Shi; Yang, Shun-Nan; Chang, Shuzhi; Li, Hui

2018-01-01

Although research on muscle dysmorphia (MD), a body dysmorphic disorder subtype, has recently increased, the causes and mechanisms underlying this disorder remain unclear. Results from studies examining disorders associated with body image suggest the involvement of self-schema in biasing attention toward specific body information. The present study examined whether individuals at higher risk of MD also display attentional biases toward specific types of body images. The validated Chinese version of the Muscle Appearance Satisfaction Scale was used to distinguish men at higher and lower risk of MD. Sixty-five adult Chinese men at higher (HRMD, n  = 33) and lower risk of MD (LRMD, n  = 32) performed a visual probe task. Initially, an image of a bodybuilder with either larger or smaller musculature was presented on one side of a central point, with a neutral image of a car exterior presented on the other side along the horizontal plane for 2,000 ms. The paired images were removed, and a visual target (a dot) was displayed in the location of one of the previously shown images. Participants were asked to indicate the location of the target, and their eye movements were recorded during the entire visual presentation. Participant reaction time and three eye movement measurements (gaze direction, first saccade latency, and first fixation duration) were recorded for use in determining attentional bias. The HRMD group revealed biases in orienting and maintaining their attention on images of bodybuilders with larger musculatures. Participants in this group consequently had a shorter reaction time in identifying the target that appeared at the location in which an image of a bodybuilder with a larger musculature had been previously displayed. They also directed their initial gaze more frequently, had shorter saccade latency, and had longer first fixation duration on images of bodybuilders with larger musculatures (all p  < .0001). In comparison, the LRMD group had

On the crustal bias of repeat stations in Romania

Directory of Open Access Journals (Sweden)

Venera Dobrica

2013-03-01

Full Text Available A magnetic induction model has been applied to recordings obtained in 2010 during the field campaigns for geomagnetic measurements at the 26 repeat stations of the Romanian secular variation network. The model is based on the observation that a variable external magnetic field induces a response of the Earth's interior not only by electromagnetic induction, but also by magnetic induction in the magnetic rocks above the Curie temperature. The model computes coefficients of a linear relationship between recorded values of a certain geomagnetic element (X, Y, Z, or F at the repeat station and recorded X, Y, Z values at a reference station (in this case, SUA observatory. Coefficients depend on magnetic permeabilities of rocks beneath the station and stand as a proxy for the anomaly bias characterizing the site. Maps of the lateral variation of this type of information were obtained and discussed.

Determination and Correction of Persistent Biases in Quantum Annealers

Science.gov (United States)

2016-08-25

for all of the qubits. Narrowing of the bias distribution. To show the correctability of the persistent biases , we ran the experiment described above...this is a promising application for bias correction . Importantly, while the J biases determined here are in general smaller than the h biases , numerical...1Scientific RepoRts | 6:18628 | DOI: 10.1038/srep18628 www.nature.com/scientificreports Determination and correction of persistent biases in quantum

Does neurocognitive function affect cognitive bias toward an emotional stimulus? Association between general attentional ability and attentional bias toward threat

OpenAIRE

Hakamata, Yuko; Matsui, Mie; Tagaya, Hirokuni

2014-01-01

Background: Although poorer cognitive performance has been found to be associated with anxiety, it remains unclear whether neurocognitive function affects biased cognitive processing toward emotional information. We investigated whether general cognitive function evaluated with a standard neuropsychological test predicts biased cognition, focusing on attentional bias toward threat. Methods: One hundred and five healthy young adults completed a dot-probe task measuring attentional bias and ...

Production bias and cluster annihilation: Why necessary?

DEFF Research Database (Denmark)

Singh, B.N.; Trinkaus, H.; Woo, C.H.

1994-01-01

the primary cluster density is high. Therefore, a sustained high swelling rate driven by production bias must involve the annihilation of primary clusters at sinks. A number of experimental observations which are unexplainable in terms of the conventional dislocation bias for monointerstitials is considered......-field approach. The production bias approach, on the other hand, is based on the physical features of the cascade damage and is therefore considered to be more appropriate for describing the damage accumulation under cascade damage conditions. However, production bias can not produce high a swelling rate when....... It is found that the production bias and cluster annihilation are necessary to explain these observations, with, in many cases, the explicit consideration of the annihilation of the primary interstitial clusters....

Approach-Induced Biases in Human Information Sampling.

Directory of Open Access Journals (Sweden)

Laurence T Hunt

2016-11-01

Full Text Available Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here, we investigated a potential role for Pavlovian approach in biasing which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled ("positive evidence approach", the selection of which information to sample ("sampling the favorite", and the interaction between information sampling and subsequent choices ("rejecting unsampled options". The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in the amount of information gathered are a stable trait across multiple gameplays and can be related to demographic measures, including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.

Gender bias affects forests worldwide

Science.gov (United States)

Marlène Elias; Susan S Hummel; Bimbika S Basnett; Carol J.P. Colfer

2017-01-01

Gender biases persist in forestry research and practice. These biases result in reduced scientific rigor and inequitable, ineffective, and less efficient policies, programs, and interventions. Drawing from a two-volume collection of current and classic analyses on gender in forests, we outline five persistent and inter-related themes: gendered governance, tree tenure,...

Investigation of local losses as a function of material removal in a large-grain superconducting niobium cavity

International Nuclear Information System (INIS)

Gianluigi Ciovati; Peter Kneisel

2006-01-01

The performance of a superconducting radio-frequency (RF) cavity made of residual resistivity ratio (RRR) > 200 large-grain niobium has been investigated as a function of material removal, between 70 and 240 ?m, by buffered chemical polishing (BCP). Temperature maps of the cavity surface at 1.7 and 2.0 K were taken for each step of chemical etching and revealed localized losses (''hot-spots''), which contribute to the degradation of the cavity quality factor as a function of the RF surface field. It was found that the number of ''hot-spots'' decreased for larger material removal. Interestingly, the losses at the ''hot-spots'' at different locations evolved differently for successive material removal. The cavity achieved peak surface magnetic fields of about of 130 mT and was limited mostly by thermal quench. By measuring the temperature dependence of the surface resistance (Rs) at low field between 4.2 K and 1.7 K, the variation of material parameters such as the energy gap at 0 K, the residual resistance and the mean free path as a function of material removal could also be investigated. This contribution presents the results of the RF tests along with the temperature maps and the analysis of the losses caused by the ''hot-spots''

Insights into earthquake hazard map performance from shaking history simulations

Science.gov (United States)

Stein, S.; Vanneste, K.; Camelbeeck, T.; Vleminckx, B.

2017-12-01

shaking — arises by chance or reflects biases in the map. Due to this problem, there are limits to how well we can expect hazard maps to predict future shaking, as well as to our ability to test the performance of a hazard map based on available observations.

Weight bias internalization across weight categories among school-aged children. Validation of the Weight Bias Internalization Scale for Children.

Science.gov (United States)

Zuba, Anna; Warschburger, Petra

2018-06-01

Anti-fat bias is widespread and is linked to the internalization of weight bias and psychosocial problems. The purpose of this study was to examine the internalization of weight bias among children across weight categories and to evaluate the psychometric properties of the Weight Bias Internalization Scale for Children (WBIS-C). Data were collected from 1484 primary school children and their parents. WBIS-C demonstrated good internal consistency (α = .86) after exclusion of Item 1. The unitary factor structure was supported using exploratory and confirmatory factor analyses (factorial validity). Girls and overweight children reported higher WBIS-C scores in comparison to boys and non-overweight peers (known-groups validity). Convergent validity was shown by significant correlations with psychosocial problems. Internalization of weight bias explained additional variance in different indicators of psychosocial well-being. The results suggest that the WBIS-C is a psychometrically sound and informative tool to assess weight bias internalization among children. Copyright © 2018 Elsevier Ltd. All rights reserved.

PLUTINO DETECTION BIASES, INCLUDING THE KOZAI RESONANCE

International Nuclear Information System (INIS)

Lawler, S. M.; Gladman, B.

2013-01-01

Because of their relative proximity within the trans-Neptunian region, the plutinos (objects in the 3:2 mean-motion resonance with Neptune) are numerous in flux-limited catalogs, and well-studied theoretically. We perform detailed modeling of the on-sky detection biases for plutinos, with special attention to those that are simultaneously in the Kozai resonance. In addition to the normal 3:2 resonant argument libration, Kozai plutinos also show periodic oscillations in eccentricity and inclination, coupled to the argument of perihelion (ω) oscillation. Due to the mean-motion resonance, plutinos avoid coming to pericenter near Neptune's current position in the ecliptic plane. Because Kozai plutinos are restricted to certain values of ω, perihelion always occurs out of the ecliptic plane, biasing ecliptic surveys against finding these objects. The observed Kozai plutino fraction f koz obs has been measured by several surveys, finding values between 8% and 25%, while the true Kozai plutino fraction f koz true has been predicted to be between 10% and 30% by different giant planet migration simulations. We show that f koz obs varies widely depending on the ecliptic latitude and longitude of the survey, so debiasing to find the true ratio is complex. Even a survey that covers most or all of the sky will detect an apparent Kozai fraction that is different from f koz true . We present a map of the on-sky plutino Kozai fraction that would be detected by all-sky flux-limited surveys. This will be especially important for the Panoramic Survey Telescope and Rapid Response System and Large Synoptic Survey Telescope projects, which may detect large numbers of plutinos as they sweep the sky. f koz true and the distribution of the orbital elements of Kozai plutinos may be a diagnostic of giant planet migration; future migration simulations should provide details on their resonant Kozai populations.

Contamination effects on fixed-bias Langmuir probes

Energy Technology Data Exchange (ETDEWEB)

Steigies, C. T. [Institut fuer Experimentelle und Angewandte Physik, Christian-Albrechts-Universitaet zu Kiel, 24098 Kiel (Germany); Barjatya, A. [Department of Physical Sciences, Embry-Riddle Aeronautical University, Daytona Beach, Florida 32114 (United States)

2012-11-15

Langmuir probes are standard instruments for plasma density measurements on many sounding rockets. These probes can be operated in swept-bias as well as in fixed-bias modes. In swept-bias Langmuir probes, contamination effects are frequently visible as a hysteresis between consecutive up and down voltage ramps. This hysteresis, if not corrected, leads to poorly determined plasma densities and temperatures. With a properly chosen sweep function, the contamination parameters can be determined from the measurements and correct plasma parameters can then be determined. In this paper, we study the contamination effects on fixed-bias Langmuir probes, where no hysteresis type effect is seen in the data. Even though the contamination is not evident from the measurements, it does affect the plasma density fluctuation spectrum as measured by the fixed-bias Langmuir probe. We model the contamination as a simple resistor-capacitor circuit between the probe surface and the plasma. We find that measurements of small scale plasma fluctuations (meter to sub-meter scale) along a rocket trajectory are not affected, but the measured amplitude of large scale plasma density variation (tens of meters or larger) is attenuated. From the model calculations, we determine amplitude and cross-over frequency of the contamination effect on fixed-bias probes for different contamination parameters. The model results also show that a fixed bias probe operating in the ion-saturation region is affected less by contamination as compared to a fixed bias probe operating in the electron saturation region.

A High-Density Genetic Linkage Map and QTL Fine Mapping for Body Weight in Crucian Carp (Carassius auratus Using 2b-RAD Sequencing

Directory of Open Access Journals (Sweden)

Haiyang Liu

2017-08-01

Full Text Available A high-resolution genetic linkage map is essential for a wide range of genetics and genomics studies such as comparative genomics analysis and QTL fine mapping. Crucian carp (Carassius auratus is widely distributed in Eurasia, and is an important aquaculture fish worldwide. In this study, a high-density genetic linkage map was constructed for crucian carp using 2b-RAD technology. The consensus map contains 8487 SNP markers, assigning to 50 linkage groups (LGs and spanning 3762.88 cM, with an average marker interval of 0.44 cM and genome coverage of 98.8%. The female map had 4410 SNPs, and spanned 3500.42 cM (0.79 cM/marker, while the male map had 4625 SNPs and spanned 3346.33 cM (0.72 cM/marker. The average recombination ratio of female to male was 2.13:1, and significant male-biased recombination suppressions were observed in LG47 and LG49. Comparative genomics analysis revealed a clear 2:1 syntenic relationship between crucian carp LGs and chromosomes of zebrafish and grass carp, and a 1:1 correspondence, but extensive chromosomal rearrangement, between crucian carp and common carp, providing evidence that crucian carp has experienced a fourth round of whole genome duplication (4R-WGD. Eight chromosome-wide QTL for body weight at 2 months after hatch were detected on five LGs, explaining 10.1–13.2% of the phenotypic variations. Potential candidate growth-related genes, such as an EGF-like domain and TGF-β, were identified within the QTL intervals. This high-density genetic map and QTL analysis supplies a basis for genome evolutionary studies in cyprinid fishes, genome assembly, and QTL fine mapping for complex traits in crucian carp.

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

Science.gov (United States)

Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not

Heuristic Biases in Mathematical Reasoning

Science.gov (United States)

Inglis, Matthew; Simpson, Adrian

2005-01-01

In this paper we briefly describe the dual process account of reasoning, and explain the role of heuristic biases in human thought. Concentrating on the so-called matching bias effect, we describe a piece of research that indicates a correlation between success at advanced level mathematics and an ability to override innate and misleading…

Improved Correction of Misclassification Bias With Bootstrap Imputation.

Science.gov (United States)

van Walraven, Carl

2018-07-01

Diagnostic codes used in administrative database research can create bias due to misclassification. Quantitative bias analysis (QBA) can correct for this bias, requires only code sensitivity and specificity, but may return invalid results. Bootstrap imputation (BI) can also address misclassification bias but traditionally requires multivariate models to accurately estimate disease probability. This study compared misclassification bias correction using QBA and BI. Serum creatinine measures were used to determine severe renal failure status in 100,000 hospitalized patients. Prevalence of severe renal failure in 86 patient strata and its association with 43 covariates was determined and compared with results in which renal failure status was determined using diagnostic codes (sensitivity 71.3%, specificity 96.2%). Differences in results (misclassification bias) were then corrected with QBA or BI (using progressively more complex methods to estimate disease probability). In total, 7.4% of patients had severe renal failure. Imputing disease status with diagnostic codes exaggerated prevalence estimates [median relative change (range), 16.6% (0.8%-74.5%)] and its association with covariates [median (range) exponentiated absolute parameter estimate difference, 1.16 (1.01-2.04)]. QBA produced invalid results 9.3% of the time and increased bias in estimates of both disease prevalence and covariate associations. BI decreased misclassification bias with increasingly accurate disease probability estimates. QBA can produce invalid results and increase misclassification bias. BI avoids invalid results and can importantly decrease misclassification bias when accurate disease probability estimates are used.

Affective Biases in Humans and Animals.

Science.gov (United States)

Robinson, E S J; Roiser, J P

Depression is one of the most common but poorly understood psychiatric conditions. Although drug treatments and psychological therapies are effective in some patients, many do not achieve full remission and some patients receive no apparent benefit. Developing new improved treatments requires a better understanding of the aetiology of symptoms and evaluation of novel therapeutic targets in pre-clinical studies. Recent developments in our understanding of the basic cognitive processes that may contribute to the development of depression and its treatment offer new opportunities for both clinical and pre-clinical research. This chapter discusses the clinical evidence supporting a cognitive neuropsychological model of depression and antidepressant efficacy, and how this information may be usefully translated to pre-clinical investigation. Studies using neuropsychological tests in depressed patients and at risk populations have revealed basic negative emotional biases and disrupted reward and punishment processing, which may also impact on non-affective cognition. These affective biases are sensitive to antidepressant treatments with early onset effects observed, suggesting an important role in recovery. This clinical work into affective biases has also facilitated back-translation to animals and the development of assays to study affective biases in rodents. These animal studies suggest that, similar to humans, rodents in putative negative affective states exhibit negative affective biases on decision-making and memory tasks. Antidepressant treatments also induce positive biases in these rodent tasks, supporting the translational validity of this approach. Although still in the early stages of development and validation, affective biases in depression have the potential to offer new insights into the clinical condition, as well as facilitating the development of more translational approaches for pre-clinical studies.

Biased managers, organizational design, and incentive provision

OpenAIRE

Moreira, Humberto Ataíde; Costa, Cristiano Machado; Ferreira, Daniel Bernardo Soares

2004-01-01

Rio de Janeiro We model the tradeoff between the balance and the strength of incentives implicit in the choice between hierarchical and matrix organizational structures. We show that managerial biases determine which structure is optimal: hierarchical forms are preferred when biases are low, while matrix structures are preferred when biases are high.

Mapping of Natural Radionuclides using Noise Adjusted Singular Value Decomposition, NASVD

DEFF Research Database (Denmark)

Aage, Helle Karina

2006-01-01

Mapping of natural radionuclides from airborne gamma spectrometry suffer from random ”noise” in the spectra due to short measurement times. This is partly compensated for by using large volume detectors to improve the counting statistics. One method of further improving the quality of the measured...... spectra is to remove from the spectra a large fraction of this random noise using a special variant of Singular Value Decomposition: Noise Adjusted Singular Value Decomposition. In 1997-1999 the natural radionuclides on the Danish Island of Bornholm were mapped using a combination of the standard 3...

Near-ultraviolet removal rates for subgingival dental calculus at different irradiation angles

Science.gov (United States)

Schoenly, Joshua E.; Seka, Wolf D.; Rechmann, Peter

2011-07-01

The laser ablation rate of subgingival dental calculus irradiated at a 400-nm-wavelength, 7.4-mJ pulse energy, and 85- and 20-deg irradiation angles is measured using laser triangulation. Three-dimensional images taken before and after irradiation create a removal map with 6-μm axial resolution. Fifteen human teeth with subgingival calculus are irradiated in vitro under a cooling water spray with an ~300-μm-diam, tenth-order super-Gaussian beam. The average subgingival calculus removal rates for irradiation at 85 and 20 deg are 11.1+/-3.6 and 11.5+/-5.9 μm/pulse, respectively, for depth removal and 4.5+/-1.7×105 and 4.8+/-2.3×105 μm3/pulse, respectively, for volume removal. The ablation rate is constant at each irradiation site but varies between sites because of the large differences in the physical and optical properties of calculus. Comparison of the average depth- and volume-removal rates does not reveal any dependence on the irradiation angle and is likely due to the surface topology of subgingival calculus samples that overshadows any expected angular dependence.

Selective near-UV ablation of subgingival dental calculus: measurement of removal rates

Science.gov (United States)

Schoenly, J. E.; Seka, W.; Rechmann, P.

2010-02-01

A noncontact profilometer (laser triangulation) was used to measure the removal rates of subgingival dental calculus irradiated with a frequency-doubled Ti:sapphire laser (60-ns pulse duration, 400-nm wavelength, 10-Hz repetition rate, 7-mJ pulse energy). Profilometer traces before and after irradiation were used to create a removal map with 4-μm axial and 15-μm transverse resolution. Twenty-three teeth (15 with calculus and 8 pristine) were irradiated at 90° and 45° under a cooling water spray with a super-Gaussian beam (~300-μm diameter). Subgingival calculus was selectively removed at 5.6 and 4.0 J/cm2 for 90° and 45°, respecetively, within a range of rates, between 2 to 9 μm/pulse. These ablation rates were constant during these exposures. For comparison, pristine cementum irradiated for 10 min at the same peak fluence and pulse repetition rate showed only craters, 15 to 50 μm deep, corresponding to an equivalent removal rate three orders of magnitude smaller than that obtained for calculus. Pristine enamel was not removed under the same irradiation conditions.

Biases in Visual, Auditory, and Audiovisual Perception of Space

Science.gov (United States)

Odegaard, Brian; Wozny, David R.; Shams, Ladan

2015-01-01

Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1) if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors), and (2) whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli). Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers) was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s) driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only improves the

Biases in Visual, Auditory, and Audiovisual Perception of Space.

Directory of Open Access Journals (Sweden)

Brian Odegaard

2015-12-01

Full Text Available Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1 if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors, and (2 whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli. Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only

Rapid recombination mapping for high-throughput genetic screens in Drosophila.

Science.gov (United States)

Sapiro, Anne L; Ihry, Robert J; Buhr, Derek L; Konieczko, Kevin M; Ives, Sarah M; Engstrom, Anna K; Wleklinski, Nicholas P; Kopish, Kristin J; Bashirullah, Arash

2013-12-09

Mutagenesis screens are a staple of classical genetics. Chemical-induced mutations, however, are often difficult and time-consuming to identify. Here, we report that recombination analysis with pairs of dominant visible markers provides a rapid and reliable strategy to map mutations in Drosophila melanogaster. This method requires only two generations and a total of six crosses in vials to estimate the genetic map position of the responsible lesion with high accuracy. This genetic map position can then be reliably used to identify the mutated gene through complementation testing with an average of nine deficiencies and Sanger sequencing. We have used this approach to successfully map a collection of mutations from an ethyl methanesulfonate-based mutagenesis screen on the third chromosome. We propose that this method also may be used in conjunction with whole-genome sequencing, particularly when multiple independent alleles of the mutated locus are not available. By facilitating the rapid identification of mutated genes, our mapping strategy removes a primary obstacle to the widespread use of powerful chemical mutagenesis screens to understand fundamental biological phenomena.

Understanding and Overcoming Implicit Gender Bias in Plastic Surgery.

Science.gov (United States)

Phillips, Nicole A; Tannan, Shruti C; Kalliainen, Loree K

2016-11-01

Although explicit sex-based discrimination has largely been deemed unacceptable in professional settings, implicit gender bias persists and results in a significant lack of parity in plastic surgery and beyond. Implicit gender bias is the result of a complex interplay of cultural and societal expectations, learned behaviors, and standardized associations. As such, both male and female surgeons are subject to its influence. A review of the literature was conducted, examining theories of gender bias, current manifestations of gender bias in plastic surgery and other fields, and interventions designed to address gender bias. Multiple studies demonstrate persistent gender bias that impacts female physicians at all levels of training. Several institutions have enacted successful interventions to identify and address gender bias. Explicit gender bias has largely disappeared, yet unconscious or implicit gender bias persists. A wide-scale commitment to addressing implicit gender bias in plastic surgery is necessary and overdue. Recommendations include immediate actions that can be undertaken on an individual basis, and changes that should be implemented at a national and international level by leaders in the field.

Galaxy bias and primordial non-Gaussianity

Energy Technology Data Exchange (ETDEWEB)

Assassi, Valentin; Baumann, Daniel [DAMTP, Cambridge University, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Schmidt, Fabian, E-mail: assassi@ias.edu, E-mail: D.D.Baumann@uva.nl, E-mail: fabians@MPA-Garching.MPG.DE [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching (Germany)

2015-12-01

We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.

Galaxy bias and primordial non-Gaussianity

International Nuclear Information System (INIS)

Assassi, Valentin; Baumann, Daniel; Schmidt, Fabian

2015-01-01

We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation

The Impact of Selection, Gene Conversion, and Biased Sampling on the Assessment of Microbial Demography.

Science.gov (United States)

Lapierre, Marguerite; Blin, Camille; Lambert, Amaury; Achaz, Guillaume; Rocha, Eduardo P C

2016-07-01

Recent studies have linked demographic changes and epidemiological patterns in bacterial populations using coalescent-based approaches. We identified 26 studies using skyline plots and found that 21 inferred overall population expansion. This surprising result led us to analyze the impact of natural selection, recombination (gene conversion), and sampling biases on demographic inference using skyline plots and site frequency spectra (SFS). Forward simulations based on biologically relevant parameters from Escherichia coli populations showed that theoretical arguments on the detrimental impact of recombination and especially natural selection on the reconstructed genealogies cannot be ignored in practice. In fact, both processes systematically lead to spurious interpretations of population expansion in skyline plots (and in SFS for selection). Weak purifying selection, and especially positive selection, had important effects on skyline plots, showing patterns akin to those of population expansions. State-of-the-art techniques to remove recombination further amplified these biases. We simulated three common sampling biases in microbiological research: uniform, clustered, and mixed sampling. Alone, or together with recombination and selection, they further mislead demographic inferences producing almost any possible skyline shape or SFS. Interestingly, sampling sub-populations also affected skyline plots and SFS, because the coalescent rates of populations and their sub-populations had different distributions. This study suggests that extreme caution is needed to infer demographic changes solely based on reconstructed genealogies. We suggest that the development of novel sampling strategies and the joint analyzes of diverse population genetic methods are strictly necessary to estimate demographic changes in populations where selection, recombination, and biased sampling are present. © The Author 2016. Published by Oxford University Press on behalf of the Society for

The electric field at hole injecting metal/organic interfaces as a cause for manifestation of exponential bias-dependent mobility

International Nuclear Information System (INIS)

Cvikl, B.

2014-01-01

It is shown that the well-known empirical exponential bias-dependent mobility is an approximation function of the relevant term emerging in the Mott–Gurney space charge limited current model when the constant non-zero electric field at the hole injecting metal/organic interface E int is taken into account. The term in question is the product of the bias-independent (but organic layer thickness-dependent) effective mobility coefficient and the algebraic function, f(λ), of the argument λ = E int /E a , where E a is the externally applied electric field. On account of the non-zero interfacial field, E int , the singularity of the spatial dependence of the hole current density, p(x), is removed. The resulting hole drift current density, j, is tested as a function of E a against a number of published room temperature hole current j–E a data sets, all characterized by good ohmic contact at the hole injecting interface. It is shown that the calculated current density provides a very good fit to the measurements within a high range of E a intervals. Low values of E a , are investigated analytically under the assumption of hole drift-diffusion. The extremely large internal electric fields at the anode/organic junction indicate drift-diffusion to be an improbable process for the structures investigated. However, a description of hole transport throughout the whole interval of experimental E a values may be obtained at low values of E a by an extended Mark–Helfrich drift model with traps occupying the exponentially distributed energy levels, followed by the extended Mott–Gurney model description within the remaining part of the E a interval. In both models the same (bias-independent) effective mobility coefficient is incorporated into the calculations. The results present evidence that within the framework of the extended Mott–Gurney expression the properly derived term should replace the empirical exponential bias-dependent mobility, making it redundant in the

Bias changing molecule–lead couple and inducing low bias negative differential resistance for electrons acceptor predicted by first-principles study

International Nuclear Information System (INIS)

Min, Y.; Fang, J.H.; Zhong, C.G.; Dong, Z.C.; Zhao, Z.Y.; Zhou, P.X.; Yao, K.L.

2015-01-01

A first-principles study of the transport properties of 3,13-dimercaptononacene–6,21-dione molecule sandwiched between two gold leads is reported. The strong effect of negative differential resistance with large peak-to-valley ratio of 710% is present under low bias. We found that bias can change molecule–lead couple and induce low bias negative differential resistance for electrons acceptor, which may promise the potential applications in molecular devices with low-power dissipation in the future. - Highlights: • Acceptor is constructed to negative differential resistor (NDR). • NDR effect is present under low bias. • Bias change molecule–lead couple and induce NDR effect

Mechanism for and method of biasing magnetic sensor

Science.gov (United States)

Kautz, David R.

2007-12-04

A magnetic sensor package having a biasing mechanism involving a coil-generated, resistor-controlled magnetic field for providing a desired biasing effect. In a preferred illustrated embodiment, the package broadly comprises a substrate; a magnetic sensor element; a biasing mechanism, including a coil and a first resistance element; an amplification mechanism; a filter capacitor element; and an encapsulant. The sensor is positioned within the coil. A current applied to the coil produces a biasing magnetic field. The biasing magnetic field is controlled by selecting a resistance value for the first resistance element which achieves the desired biasing effect. The first resistance element preferably includes a plurality of selectable resistors, the selection of one or more of which sets the resistance value.

Evidence of sex-bias in gene expression in the brain transcriptome of two populations of rainbow trout (Oncorhynchus mykiss) with divergent life histories.

Science.gov (United States)

Hale, Matthew C; McKinney, Garrett J; Thrower, Frank P; Nichols, Krista M

2018-01-01

Sex-bias in gene expression is a mechanism that can generate phenotypic variance between the sexes, however, relatively little is known about how patterns of sex-bias vary during development, and how variable sex-bias is between different populations. To that end, we measured sex-bias in gene expression in the brain transcriptome of rainbow trout (Oncorhynchus mykiss) during the first two years of development. Our sampling included from the fry stage through to when O. mykiss either migrate to the ocean or remain resident and undergo sexual maturation. Samples came from two F1 lines: One from migratory steelhead trout and one from resident rainbow trout. All samples were reared in a common garden environment and RNA sequencing (RNA-seq) was used to estimate patterns of gene expression. A total of 1,716 (4.6% of total) genes showed evidence of sex-bias in gene expression in at least one time point. The majority (96.7%) of sex-biased genes were differentially expressed during the second year of development, indicating that patterns of sex-bias in expression are tied to key developmental events, such as migration and sexual maturation. Mapping of differentially expressed genes to the O. mykiss genome revealed that the X chromosome is enriched for female upregulated genes, and this may indicate a lack of dosage compensation in rainbow trout. There were many more sex-biased genes in the migratory line than the resident line suggesting differences in patterns of gene expression in the brain between populations subjected to different forces of selection. Overall, our results suggest that there is considerable variation in the extent and identity of genes exhibiting sex-bias during the first two years of life. These differentially expressed genes may be connected to developmental differences between the sexes, and/or between adopting a resident or migratory life history.

Mood-congruent free recall bias in anxious individuals is not a consequence of response bias.

Science.gov (United States)

Russo, Riccardo; Whittuck, Dora; Roberson, Debi; Dutton, Kevin; Georgiou, George; Fox, Elaine

2006-05-01

The status of mood-congruent free recall bias in anxious individuals was evaluated following incidental encoding of target words. Individuals with high and low levels of trait anxiety completed a modified Stroop task, which revealed an attentional bias for threat-related stimuli in anxious individuals. This group was significantly slower in naming the colour in which threat-related words were displayed compared to neutral words. In a subsequent free recall test for the words used in the modified Stroop task, anxious individuals recalled more threat-related words compared to low-anxious people. This difference was significant even when controlling for the false recall of items that had not been presented during study. These results support the view put forward by Russo, Fox, Bellinger, and Nguyen-Van-Tam (2001) that mood-congruent free recall bias in anxious individuals can be observed if the target material is encoded at a relatively shallow level. Moreover, contrary to Dowens and Calvo (2003), the current results show that the memory advantage for threat-related information in anxious individuals is not a consequence of response bias.

White and Black American Children’s Implicit Intergroup Bias

Science.gov (United States)

Newheiser, Anna-Kaisa; Olson, Kristina R.

2011-01-01

Despite a decline in explicit prejudice, adults and children from majority groups (e.g., White Americans) often express bias implicitly, as assessed by the Implicit Association Test. In contrast, minority-group (e.g., Black American) adults on average show no bias on the IAT. In the present research, representing the first empirical investigation of whether Black children’s IAT responses parallel those of Black adults, we examined implicit bias in 7–11-year-old White and Black American children. Replicating previous findings with adults, whereas White children showed a robust ingroup bias, Black children showed no bias. Additionally, we investigated the role of valuing status in the development of implicit bias. For Black children, explicit preference for high status predicted implicit outgroup bias: Black children who explicitly expressed high preference for rich (vs. poor) people showed an implicit preference for Whites comparable in magnitude to White children’s ingroup bias. Implications for research on intergroup bias are discussed. PMID:22184478

Fecal Coliform Removal by River Networks

Science.gov (United States)

Huang, T.; Wollheim, W. M.; Stewart, R. J.

2015-12-01

concentrations at both low and high flow due to dilution and in-stream processing. Mapping the spatial and temporal distribution fecal coliform sources and removal can help improve water quality management.

Intraoperative Functional Mapping and Monitoring during Glioma Surgery

Science.gov (United States)

SAITO, Taiichi; MURAGAKI, Yoshihiro; MARUYAMA, Takashi; TAMURA, Manabu; NITTA, Masayuki; OKADA, Yoshikazu

2015-01-01

Glioma surgery represents a significant advance with respect to improving resection rates using new surgical techniques, including intraoperative functional mapping, monitoring, and imaging. Functional mapping under awake craniotomy can be used to detect individual eloquent tissues of speech and/or motor functions in order to prevent unexpected deficits and promote extensive resection. In addition, monitoring the patient’s neurological findings during resection is also very useful for maximizing the removal rate and minimizing deficits by alarming that the touched area is close to eloquent regions and fibers. Assessing several types of evoked potentials, including motor evoked potentials (MEPs), sensory evoked potentials (SEPs) and visual evoked potentials (VEPs), is also helpful for performing surgical monitoring in patients under general anesthesia (GA). We herein review the utility of intraoperative mapping and monitoring the assessment of neurological findings, with a particular focus on speech and the motor function, in patients undergoing glioma surgery. PMID:25744346

Amazonian landscapes and the bias in field studies of forest structure and biomass.

Science.gov (United States)

Marvin, David C; Asner, Gregory P; Knapp, David E; Anderson, Christopher B; Martin, Roberta E; Sinca, Felipe; Tupayachi, Raul

2014-12-02

Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9-98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy.

Mapping out Map Libraries

Directory of Open Access Journals (Sweden)

Ferjan Ormeling

2008-09-01

Full Text Available Discussing the requirements for map data quality, map users and their library/archives environment, the paper focuses on the metadata the user would need for a correct and efficient interpretation of the map data. For such a correct interpretation, knowledge of the rules and guidelines according to which the topographers/cartographers work (such as the kind of data categories to be collected, and the degree to which these rules and guidelines were indeed followed are essential. This is not only valid for the old maps stored in our libraries and archives, but perhaps even more so for the new digital files as the format in which we now have to access our geospatial data. As this would be too much to ask from map librarians/curators, some sort of web 2.0 environment is sought where comments about data quality, completeness and up-to-dateness from knowledgeable map users regarding the specific maps or map series studied can be collected and tagged to scanned versions of these maps on the web. In order not to be subject to the same disadvantages as Wikipedia, where the ‘communis opinio’ rather than scholarship, seems to be decisive, some checking by map curators of this tagged map use information would still be needed. Cooperation between map curators and the International Cartographic Association ( ICA map and spatial data use commission to this end is suggested.

New Angle on the Parton Distribution Functions: Self-Organizing Maps

International Nuclear Information System (INIS)

Honkanen, H.; Liuti, S.

2009-01-01

Neural network (NN) algorithms have been recently applied to construct Parton Distribution Function (PDF) parametrizations, providing an alternative to standard global fitting procedures. Here we explore a novel technique using Self-Organizing Maps (SOMs). SOMs are a class of clustering algorithms based on competitive learning among spatially-ordered neurons. We train our SOMs with stochastically generated PDF samples. On every optimization iteration the PDFs are clustered on the SOM according to a user-defined feature and the most promising candidates are used as a seed for the subsequent iteration using the topology of the map to guide the PDF generating process. Our goal is a fitting procedure that, at variance with the standard neural network approaches, will allow for an increased control of the systematic bias by enabling user interaction in the various stages of the process.

A bias-corrected CMIP5 dataset for Africa using the CDF-t method - a contribution to agricultural impact studies

Science.gov (United States)

Moise Famien, Adjoua; Janicot, Serge; Delfin Ochou, Abe; Vrac, Mathieu; Defrance, Dimitri; Sultan, Benjamin; Noël, Thomas

2018-03-01

The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950-2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

On the relative independence of thinking biases and cognitive ability.

Science.gov (United States)

Stanovich, Keith E; West, Richard F

2008-04-01

In 7 different studies, the authors observed that a large number of thinking biases are uncorrelated with cognitive ability. These thinking biases include some of the most classic and well-studied biases in the heuristics and biases literature, including the conjunction effect, framing effects, anchoring effects, outcome bias, base-rate neglect, "less is more" effects, affect biases, omission bias, myside bias, sunk-cost effect, and certainty effects that violate the axioms of expected utility theory. In a further experiment, the authors nonetheless showed that cognitive ability does correlate with the tendency to avoid some rational thinking biases, specifically the tendency to display denominator neglect, probability matching rather than maximizing, belief bias, and matching bias on the 4-card selection task. The authors present a framework for predicting when cognitive ability will and will not correlate with a rational thinking tendency. (c) 2008 APA, all rights reserved.

AutoMap User’s Guide 2011

Science.gov (United States)

2011-06-13

the Generalization Thesaurus but leaves all other concepts intact. If useThesauriContentOnly="y" then AutoMap replaces concepts but removes all...crf.sourceforge.net/ google-collect- 1.0-rc1.jar Guava http://code.google.com/p/ guava -libraries/ The Apache Software License, Version 2.0 htmlparser.jar...He lives on a dairy farm. He considers it a good life. Would he ever consider leaving ? Direct Adjacency Ted lives United States America. He lives

Assessing the extent of non-stationary biases in GCMs

Science.gov (United States)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-06-01

General circulation models (GCMs) are the main tools for estimating changes in the climate for the future. The imperfect representation of climate models introduces biases in the simulations that need to be corrected prior to their use for impact assessments. Bias correction methods generally assume that the bias calculated over the historical period does not change and can be applied to the future. This study investigates this assumption by considering the extent and nature of bias non-stationarity using 20th century precipitation and temperature simulations from six CMIP5 GCMs across Australia. Four statistics (mean, standard deviation, 10th and 90th quantiles) in monthly and seasonal biases are obtained for three different time window lengths (10, 25 and 33 years) to examine the properties of bias over time. This approach is repeated for two different phases of the Interdecadal Pacific Oscillation (IPO), which is known to have strong influences on the Australian climate. It is found that bias non-stationarity at decadal timescales is indeed an issue over some of Australia for some GCMs. When considering interdecadal variability there are significant difference in the bias between positive and negative phases of the IPO. Regional analyses confirmed these findings with the largest differences seen on the east coast of Australia, where IPO impacts tend to be the strongest. The nature of the bias non-stationarity found in this study suggests that it will be difficult to modify existing bias correction approaches to account for non-stationary biases. A more practical approach for impact assessments that use bias correction maybe to use a selection of GCMs where the assumption of bias non-stationarity holds.

Assessment of tropospheric delay mapping function models in Egypt: Using PTD database model

Science.gov (United States)

Abdelfatah, M. A.; Mousa, Ashraf E.; El-Fiky, Gamal S.

2018-06-01

For space geodetic measurements, estimates of tropospheric delays are highly correlated with site coordinates and receiver clock biases. Thus, it is important to use the most accurate models for the tropospheric delay to reduce errors in the estimates of the other parameters. Both the zenith delay value and mapping function should be assigned correctly to reduce such errors. Several mapping function models can treat the troposphere slant delay. The recent models were not evaluated for the Egyptian local climate conditions. An assessment of these models is needed to choose the most suitable one. The goal of this paper is to test the quality of global mapping function which provides high consistency with precise troposphere delay (PTD) mapping functions. The PTD model is derived from radiosonde data using ray tracing, which consider in this paper as true value. The PTD mapping functions were compared, with three recent total mapping functions model and another three separate dry and wet mapping function model. The results of the research indicate that models are very close up to zenith angle 80°. Saastamoinen and 1/cos z model are behind accuracy. Niell model is better than VMF model. The model of Black and Eisner is a good model. The results also indicate that the geometric range error has insignificant effect on slant delay and the fluctuation of azimuth anti-symmetric is about 1%.

Effects of Bias Modification Training in Binge Eating Disorder.

Science.gov (United States)

Schmitz, Florian; Svaldi, Jennifer

2017-09-01

Food-related attentional biases have been identified as maintaining factors in binge eating disorder (BED) as they can trigger a binge episode. Bias modification training may reduce symptoms, as it has been shown to be successful in other appetitive disorders. The aim of this study was to assess and modify food-related biases in BED. It was tested whether biases could be increased and decreased by means of a modified dot-probe paradigm, how long such bias modification persisted, and whether this affected subjective food craving. Participants were randomly assigned to a bias enhancement (attend to food stimulus) group or to a bias reduction (avoid food stimulus) group. Food-related attentional bias was found to be successfully reduced in the bias-reduction group, and effects persisted briefly. Additionally, subjective craving for food was influenced by the intervention, and possible mechanisms are discussed. Given these promising initial results, future research should investigate boundary conditions of the experimental intervention to understand how it could complement treatment of BED. Copyright © 2017. Published by Elsevier Ltd.

Attentional bias in math anxiety.

Science.gov (United States)

Rubinsten, Orly; Eidlin, Hili; Wohl, Hadas; Akibli, Orly

2015-01-01

Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety (MA) as well (i.e., a persistent negative reaction to math). Twenty seven participants (14 with high levels of MA and 13 with low levels of MA) were presented with a novel computerized numerical version of the well established dot probe task. One of six types of prime stimuli, either math related or typically neutral, was presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks) that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks). Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in MA. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words). These findings suggest that attentional bias is linked to unduly intense MA symptoms.

A retrieval-based approach to eliminating hindsight bias.

Science.gov (United States)

Van Boekel, Martin; Varma, Keisha; Varma, Sashank

2017-03-01

Individuals exhibit hindsight bias when they are unable to recall their original responses to novel questions after correct answers are provided to them. Prior studies have eliminated hindsight bias by modifying the conditions under which original judgments or correct answers are encoded. Here, we explored whether hindsight bias can be eliminated by manipulating the conditions that hold at retrieval. Our retrieval-based approach predicts that if the conditions at retrieval enable sufficient discrimination of memory representations of original judgments from memory representations of correct answers, then hindsight bias will be reduced or eliminated. Experiment 1 used the standard memory design to replicate the hindsight bias effect in middle-school students. Experiments 2 and 3 modified the retrieval phase of this design, instructing participants beforehand that they would be recalling both their original judgments and the correct answers. As predicted, this enabled participants to form compound retrieval cues that discriminated original judgment traces from correct answer traces, and eliminated hindsight bias. Experiment 4 found that when participants were not instructed beforehand that they would be making both recalls, they did not form discriminating retrieval cues, and hindsight bias returned. These experiments delineate the retrieval conditions that produce-and fail to produce-hindsight bias.

Large-scale assembly bias of dark matter halos

Energy Technology Data Exchange (ETDEWEB)

Lazeyras, Titouan; Musso, Marcello; Schmidt, Fabian, E-mail: titouan@mpa-garching.mpg.de, E-mail: mmusso@sas.upenn.edu, E-mail: fabians@mpa-garching.mpg.de [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching (Germany)

2017-03-01

We present precise measurements of the assembly bias of dark matter halos, i.e. the dependence of halo bias on other properties than the mass, using curved 'separate universe' N-body simulations which effectively incorporate an infinite-wavelength matter overdensity into the background density. This method measures the LIMD (local-in-matter-density) bias parameters b {sub n} in the large-scale limit. We focus on the dependence of the first two Eulerian biases b {sup E} {sup {sub 1}} and b {sup E} {sup {sub 2}} on four halo properties: the concentration, spin, mass accretion rate, and ellipticity. We quantitatively compare our results with previous works in which assembly bias was measured on fairly small scales. Despite this difference, our findings are in good agreement with previous results. We also look at the joint dependence of bias on two halo properties in addition to the mass. Finally, using the excursion set peaks model, we attempt to shed new insights on how assembly bias arises in this analytical model.

Dual-electrode biasing experiments in KT-5C device

International Nuclear Information System (INIS)

Yu Yi; Lu Ronghua; Wang Chen; Pan Geshen; Wen Yizhi; Yu Changxuan; Ma Jinxiu; Wan Shude; Liu Wandong

2005-01-01

Based on the single biasing electrode experiments to optimize the confinement of plasma in the device of KT-5C tokamak, dual-biasing electrodes were inserted into the KT5C plasma for the first time to explore the enhancement of the effects of biasing and the mechanisms of the biasing. By means of applying different combinations of biasing voltages to the dual electrodes, the changes in E r , which is the key factor for boosting up the Er x B flow shear, were observed. The time evolution showed the inner electrode played a major role in dual-biasing, for it always drew a larger current than the outer one. The outer electrode made little influence. It turned out that the dual-biasing electrodes were as effective as a single one, in improving plasma confinement, for the mechanism of biasing was essentially an edge effect. (author)

Bias-Correction in Vector Autoregressive Models: A Simulation Study

Directory of Open Access Journals (Sweden)

Tom Engsted

2014-03-01

Full Text Available We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find that it compares very favorably in non-stationary models.

Biased lineups: sequential presentation reduces the problem.

Science.gov (United States)

Lindsay, R C; Lea, J A; Nosworthy, G J; Fulford, J A; Hector, J; LeVan, V; Seabrook, C

1991-12-01

Biased lineups have been shown to increase significantly false, but not correct, identification rates (Lindsay, Wallbridge, & Drennan, 1987; Lindsay & Wells, 1980; Malpass & Devine, 1981). Lindsay and Wells (1985) found that sequential lineup presentation reduced false identification rates, presumably by reducing reliance on relative judgment processes. Five staged-crime experiments were conducted to examine the effect of lineup biases and sequential presentation on eyewitness recognition accuracy. Sequential lineup presentation significantly reduced false identification rates from fair lineups as well as from lineups biased with regard to foil similarity, instructions, or witness attire, and from lineups biased in all of these ways. The results support recommendations that police present lineups sequentially.

Estimating floodwater depths from flood inundation maps and topography

Science.gov (United States)

Cohen, Sagy; Brakenridge, G. Robert; Kettner, Albert; Bates, Bradford; Nelson, Jonathan M.; McDonald, Richard R.; Huang, Yu-Fen; Munasinghe, Dinuke; Zhang, Jiaqi

2018-01-01

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.

Assessment of radiation maps during activated divertor moving in the ITER building

International Nuclear Information System (INIS)

Ying Dongchuan; Zeng Qin; Qiu Yuefeng; Dang Tongqiang; Wu Yican; Loughlin, Michael

2011-01-01

As the main interface components between plasma and vacuum vessel, the divertor is foreseen to be removed to the hot cell for refurbishment during the 20 years of ITER operation. During this process, the activated divertor will cause a large increase of radiation in the ITER building. 3D analysis has been performed to assess the radiation maps throughout the ITER building for assisting the shielding design for personnel and sensitive equipment. The activation of the divertor has been determined by coupled neutron transport and inventory calculations, radiation maps have been obtained from gamma transport calculations. The neutron and gamma transport calculations have been performed by MCNP5 code with FENDL2.1library. The inventory calculations have been performed by FISPACT2007 code with EAF-2007 library. The results of these 3D decay gamma radiation maps are presented by pictures in this paper, including the biological dose maps and maps of heat deposition in electronic equipment.

Students' gender bias in teaching evaluations

Directory of Open Access Journals (Sweden)

Narissra Punyanunt-Carter

2015-09-01

Full Text Available The goal of this study was to investigate if there is gender bias in student evaluations. Researchers administered a modified version of the teacher evaluation forms to 58 students (male=30; female=28 in a basic introductory communications class. Half the class was instructed to fill out the survey about a male professor, and the other half a female professor. Researchers broke down the evaluation results question by question in order to give a detailed account of the findings. Results revealed that there is certainly some gender bias at work when students evaluate their instructors. It was also found that gender bias does not significantly affect the evaluations. The results align with other findings in the available literature, which point to some sort of pattern regarding gender bias in evaluations, but it still seems to be inconsequential.  DOI: 10.18870/hlrc.v5i3.234

Quantitative mapping of chemical compositions with MRI using compressed sensing.

Science.gov (United States)

von Harbou, Erik; Fabich, Hilary T; Benning, Martin; Tayler, Alexander B; Sederman, Andrew J; Gladden, Lynn F; Holland, Daniel J

2015-12-01

In this work, a magnetic resonance (MR) imaging method for accelerating the acquisition time of two dimensional concentration maps of different chemical species in mixtures by the use of compressed sensing (CS) is presented. Whilst 2D-concentration maps with a high spatial resolution are prohibitively time-consuming to acquire using full k-space sampling techniques, CS enables the reconstruction of quantitative concentration maps from sub-sampled k-space data. First, the method was tested by reconstructing simulated data. Then, the CS algorithm was used to reconstruct concentration maps of binary mixtures of 1,4-dioxane and cyclooctane in different samples with a field-of-view of 22mm and a spatial resolution of 344μm×344μm. Spiral based trajectories were used as sampling schemes. For the data acquisition, eight scans with slightly different trajectories were applied resulting in a total acquisition time of about 8min. In contrast, a conventional chemical shift imaging experiment at the same resolution would require about 17h. To get quantitative results, a careful weighting of the regularisation parameter (via the L-curve approach) or contrast-enhancing Bregman iterations are applied for the reconstruction of the concentration maps. Both approaches yield relative errors of the concentration map of less than 2mol-% without any calibration prior to the measurement. The accuracy of the reconstructed concentration maps deteriorates when the reconstruction model is biased by systematic errors such as large inhomogeneities in the static magnetic field. The presented method is a powerful tool for the fast acquisition of concentration maps that can provide valuable information for the investigation of many phenomena in chemical engineering applications. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Simulation of HPIB propagation in biased charge collector

International Nuclear Information System (INIS)

Li Hongyu; Qiu Aici

2004-01-01

A 2.5D PIC simulation using KARAT code for inner charge propagation within biased charge collector for measuring HPIB is presented. The simulation results indicate that the charges were neutralized but the current non-neutralized in the biased charge collector. The influence of ions collected vs biased voltage of the collector was also simulated. -800 V biased voltage can meet the measurement of 500 keV HPIB, and this is consistent with the experimental results

Exchange bias effect in Au-Fe3O4 nanocomposites

International Nuclear Information System (INIS)

Chandra, Sayan; Frey Huls, N A; Phan, M H; Srinath, S; Srikanth, H; Garcia, M A; Lee, Youngmin; Wang, Chao; Sun, Shouheng; 2UB, Universitat de Barcelona, Avenida Diagonal 647, E-08028 Barcelona (Spain))" data-affiliation=" (Departament de Física Fonamental and Institut de Nanociència i Nanotecnologia IN2UB, Universitat de Barcelona, Avenida Diagonal 647, E-08028 Barcelona (Spain))" >Iglesias, Òscar

2014-01-01

We report exchange bias (EB) effect in the Au-Fe 3 O 4 composite nanoparticle system, where one or more Fe 3 O 4 nanoparticles are attached to an Au seed particle forming ‘dimer’ and ‘cluster’ morphologies, with the clusters showing much stronger EB in comparison with the dimers. The EB effect develops due to the presence of stress at the Au-Fe 3 O 4 interface which leads to the generation of highly disordered, anisotropic surface spins in the Fe 3 O 4 particle. The EB effect is lost with the removal of the interfacial stress. Our atomistic Monte Carlo studies are in excellent agreement with the experimental results. These results show a new path towards tuning EB in nanostructures, namely controllably creating interfacial stress, and opens up the possibility of tuning the anisotropic properties of biocompatible nanoparticles via a controllable exchange coupling mechanism. (paper)

Selectivity and stoichiometry boosting of beta-cyclodextrin in cationic/anionic surfactant systems: when host-guest equilibrium meets biased aggregation equilibrium.

Science.gov (United States)

Jiang, Lingxiang; Yu, Caifang; Deng, Manli; Jin, Changwen; Wang, Yilin; Yan, Yun; Huang, Jianbin

2010-02-18

Cationic surfactant/anionic surfactant/beta-CD ternary aqueous systems provide a platform for the coexistence of the host-guest (beta-CD/surfactant) equilibrium and the biased aggregation (monomeric/aggregated surfactants) equilibrium. We report here that the interplay between the two equilibria dominates the systems as follows. (1) The biased aggregation equilibrium imposes an apparent selectivity on the host-guest equilibrium, namely, beta-CD has to always selectively bind the major surfactant (molar fraction > 0.5) even if binding constants of beta-CD to the pair of surfactants are quite similar. (2) In return, the host-guest equilibrium amplifies the bias of the aggregation equilibrium, that is, the selective binding partly removes the major surfactant from the aggregates and leaves the aggregate composition approaching the electroneutral mixing stoichiometry. (3) This composition variation enhances electrostatic attractions between oppositely charged surfactant head groups, thus resulting in less-curved aggregates. In particular, the present apparent host-guest selectivity is of remarkably high values, and the selectivity stems from the bias of the aggregation equilibrium rather than the difference in binding constants. Moreover, beta-CD is defined as a "stoichiometry booster" for the whole class of cationic/anionic surfactant systems, which provides an additional degree of freedom to directly adjust aggregate compositions of the systems. The stoichiometry boosting of the compositions can in turn affect or even determine microstructures and macroproperties of the systems.

Sci—Thur AM: YIS - 08: Constructing an Attenuation map for a PET/MR Breast coil

International Nuclear Information System (INIS)

Patrick, John C.; So, Aaron; Butler, John; Faul, David; Yartsev, Slav; Thompson, Terry; Prato, Frank S.; Gaede, Stewart

2014-01-01

In 2013, around 23000 Canadian women and 200 Canadian men were diagnosed with breast cancer. An estimated 5100 women and 55 men died from the disease. Using the sensitivity of MRI with the selectivity of PET, PET/MRI combines anatomical and functional information within the same scan and could help with early detection in high-risk patients. MRI requires radiofrequency coils for transmitting energy and receiving signal but the breast coil attenuates PET signal. To correct for this PET attenuation, a 3-dimensional map of linear attenuation coefficients (μ-map) of the breast coil must be created and incorporated into the PET reconstruction process. Several approaches have been proposed for building hardware μ-maps, some of which include the use of conventional kVCT and Dual energy CT. These methods can produce high resolution images based on the electron densities of materials that can be converted into μ-maps. However, imaging hardware containing metal components with photons in the kV range is susceptible to metal artifacts. These artifacts can compromise the accuracy of the resulting μ-map and PET reconstruction; therefore high-Z components should be removed. We propose a method for calculating μ-maps without removing coil components, based on megavoltage (MV) imaging with a linear accelerator that has been detuned for imaging at 1.0MeV. Containers of known geometry with F18 were placed in the breast coil for imaging. A comparison between reconstructions based on the different μ-map construction methods was made. PET reconstructions with our method show a maximum of 6% difference over the existing kVCT-based reconstructions

State Estimation for a Biological Phosphorus Removal Process using an Asymptotic Observer

DEFF Research Database (Denmark)

Larose, Claude Alain; Jørgensen, Sten Bay

2001-01-01

This study investigated the use of an asymptotic observer for state estimation in a continuous biological phosphorus removal process. The estimated states are the concentration of heterotrophic, autotrophic, and phosphorus accumulating organisms, polyphosphate, glycogen and PHA. The reaction scheme...... if the convergence, driven by the dilution rate, was slow (from 15 to 60 days). The propagation of the measurement noise and a bias in the estimation of glycogen and PHA could be the result of the high condition number of one of the matrices used in the algorithm of the asymptotic observer for the aerated tanks....

New Trends in Magnetic Exchange Bias

Science.gov (United States)

Mougin, Alexandra; Mangin, Stéphane; Bobo, Jean-Francois; Loidl, Alois

2005-05-01

The study of layered magnetic structures is one of the hottest topics in magnetism due to the growing attraction of applications in magnetic sensors and magnetic storage media, such as random access memory. For almost half a century, new discoveries have driven researchers to re-investigate magnetism in thin film structures. Phenomena such as giant magnetoresistance, tunneling magnetoresistance, exchange bias and interlayer exchange coupling led to new ideas to construct devices, based not only on semiconductors but on a variety of magnetic materials Upon cooling fine cobalt particles in a magnetic field through the Néel temperature of their outer antiferromagnetic oxide layer, Meiklejohn and Bean discovered exchange bias in 1956. The exchange bias effect through which an antiferromagnetic AF layer can cause an adjacent ferromagnetic F layer to develop a preferred direction of magnetization, is widely used in magnetoelectronics technology to pin the magnetization of a device reference layer in a desired direction. However, the origin and effects due to exchange interaction across the interface between antiferromagneic and ferromagnetic layers are still debated after about fifty years of research, due to the extreme difficulty associated with the determination of the magnetic interfacial structure in F/AF bilayers. Indeed, in an AF/F bilayer system, the AF layer acts as “the invisible man” during conventional magnetic measurements and the presence of the exchange coupling is evidenced indirectly through the unusual behavior of the adjacent F layer. Basically, the coercive field of the F layer increases in contact with the AF and, in some cases, its hysteresis loop is shifted by an amount called exchange bias field. Thus, AF/F exchange coupling generates a new source of anisotropy in the F layer. This induced anisotropy strongly depends on basic features such as the magnetocrystalline anisotropy, crystallographic and spin structures, defects, domain patterns etc

Implementation of linear bias corrections for calorimeters at Mound

International Nuclear Information System (INIS)

Barnett, T.M.

1993-01-01

In the past, Mound has generally made relative bias corrections as part of the calibration of individual calorimeters. The correction made was the same over the entire operating range of the calorimeter, regardless of the magnitude of the range. Recently, an investigation was performed to check the relevancy of using linear bias corrections to calibrate the calorimeters. The bias is obtained by measuring calibrated plutonium and/or electrical heat standards over the operating range of the calorimeter. The bias correction is then calculated using a simple least squares fit (y = mx + b) of the bias in milliwatts over the operating range of the calorimeter in watts. The equation used is B i = B 0 + (B w * W m ), where B i is the bias at any given power in milliwatts, B 0 is the intercept (absolute bias in milliwatts), B w is the slope (relative bias in milliwatts per watt), and W m is the measured power in watts. The results of the study showed a decrease in the random error of bias corrected data for most of the calorimeters which are operated over a large wattage range (greater than an order of magnitude). The linear technique for bias correction has been fully implemented at Mound and has been included in the Technical Manual, ''A Measurement Control Program for Radiometric Calorimeters at Mound'' (MD-21900)

Error and Uncertainty in the Accuracy Assessment of Land Cover Maps

Science.gov (United States)

Sarmento, Pedro Alexandre Reis

Traditionally the accuracy assessment of land cover maps is performed through the comparison of these maps with a reference database, which is intended to represent the "real" land cover, being this comparison reported with the thematic accuracy measures through confusion matrixes. Although, these reference databases are also a representation of reality, containing errors due to the human uncertainty in the assignment of the land cover class that best characterizes a certain area, causing bias in the thematic accuracy measures that are reported to the end users of these maps. The main goal of this dissertation is to develop a methodology that allows the integration of human uncertainty present in reference databases in the accuracy assessment of land cover maps, and analyse the impacts that uncertainty may have in the thematic accuracy measures reported to the end users of land cover maps. The utility of the inclusion of human uncertainty in the accuracy assessment of land cover maps is investigated. Specifically we studied the utility of fuzzy sets theory, more precisely of fuzzy arithmetic, for a better understanding of human uncertainty associated to the elaboration of reference databases, and their impacts in the thematic accuracy measures that are derived from confusion matrixes. For this purpose linguistic values transformed in fuzzy intervals that address the uncertainty in the elaboration of reference databases were used to compute fuzzy confusion matrixes. The proposed methodology is illustrated using a case study in which the accuracy assessment of a land cover map for Continental Portugal derived from Medium Resolution Imaging Spectrometer (MERIS) is made. The obtained results demonstrate that the inclusion of human uncertainty in reference databases provides much more information about the quality of land cover maps, when compared with the traditional approach of accuracy assessment of land cover maps. None

Revealing the Cosmic Web-dependent Halo Bias

Science.gov (United States)

Yang, Xiaohu; Zhang, Youcai; Lu, Tianhuan; Wang, Huiyuan; Shi, Feng; Tweed, Dylan; Li, Shijie; Luo, Wentao; Lu, Yi; Yang, Lei

2017-10-01

Halo bias is the one of the key ingredients of the halo models. It was shown at a given redshift to be only dependent, to the first order, on the halo mass. In this study, four types of cosmic web environments—clusters, filaments, sheets, and voids—are defined within a state-of-the-art high-resolution N-body simulation. Within these environments, we use both halo-dark matter cross correlation and halo-halo autocorrelation functions to probe the clustering properties of halos. The nature of the halo bias differs strongly between the four different cosmic web environments described here. With respect to the overall population, halos in clusters have significantly lower biases in the {10}11.0˜ {10}13.5 {h}-1 {M}⊙ mass range. In other environments, however, halos show extremely enhanced biases up to a factor 10 in voids for halos of mass ˜ {10}12.0 {h}-1 {M}⊙ . Such a strong cosmic web environment dependence in the halo bias may play an important role in future cosmological and galaxy formation studies. Within this cosmic web framework, the age dependency of halo bias is found to be only significant in clusters and filaments for relatively small halos ≲ {10}12.5 {h}-1 {M}⊙ .

Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor

Directory of Open Access Journals (Sweden)

Heegwang Kim

2017-12-01

Full Text Available Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system.

Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor.

Science.gov (United States)

Kim, Heegwang; Park, Jinho; Park, Hasil; Paik, Joonki

2017-12-09

Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system.

Dwalingen in de methodologie. II. Bias door vragenlijsten

DEFF Research Database (Denmark)

Pouwer, F; Van Der Ploeg, Henk M; Bramsen, I

1998-01-01

Some characteristics of self-report questionnaires can result in bias in responding. When a test item or a questionnaire is biased, the observed scores form an imprecise measurement of reality as a consequence of systematic errors of measurement. Causes of such bias are: unclear instructions, vague...

Non-Gaussian bias: insights from discrete density peaks

CERN Document Server

Desjacques, Vincent; Riotto, Antonio

2013-01-01

Corrections induced by primordial non-Gaussianity to the linear halo bias can be computed from a peak-background split or the widespread local bias model. However, numerical simulations clearly support the prediction of the former, in which the non-Gaussian amplitude is proportional to the linear halo bias. To understand better the reasons behind the failure of standard Lagrangian local bias, in which the halo overdensity is a function of the local mass overdensity only, we explore the effect of a primordial bispectrum on the 2-point correlation of discrete density peaks. We show that the effective local bias expansion to peak clustering vastly simplifies the calculation. We generalize this approach to excursion set peaks and demonstrate that the resulting non-Gaussian amplitude, which is a weighted sum of quadratic bias factors, precisely agrees with the peak-background split expectation, which is a logarithmic derivative of the halo mass function with respect to the normalisation amplitude. We point out tha...

Using Environmental Variables for Studying of the Quality of Sampling in Soil Mapping

OpenAIRE

A. Jafari; Norair Toomanian; R. Taghizadeh Mehrjerdi

2016-01-01

Introduction: Methods of soil survey are generally empirical and based on the mental development of the surveyor, correlating soil with underlying geology, landforms, vegetation and air-photo interpretation. Since there are no statistical criteria for traditional soil sampling; this may lead to bias in the areas being sampled. In digital soil mapping, soil samples may be used to elaborate quantitative relationships or models between soil attributes and soil covariates. Because the relationshi...

Automated mapping of soybean and corn using phenology

Science.gov (United States)

Zhong, Liheng; Hu, Lina; Yu, Le; Gong, Peng; Biging, Gregory S.

2016-09-01

For the two of the most important agricultural commodities, soybean and corn, remote sensing plays a substantial role in delivering timely information on the crop area for economic, environmental and policy studies. Traditional long-term mapping of soybean and corn is challenging as a result of the high cost of repeated training data collection, the inconsistency in image process and interpretation, and the difficulty of handling the inter-annual variability of weather and crop progress. In this study, we developed an automated approach to map soybean and corn in the state of Paraná, Brazil for crop years 2010-2015. The core of the approach is a decision tree classifier with rules manually built based on expert interaction for repeated use. The automated approach is advantageous for its capacity of multi-year mapping without the need to re-train or re-calibrate the classifier. Time series MODerate-resolution Imaging Spectroradiometer (MODIS) reflectance product (MCD43A4) were employed to derive vegetation phenology to identify soybean and corn based on crop calendar. To deal with the phenological similarity between soybean and corn, the surface reflectance of the shortwave infrared band scaled to a phenological stage was used to fully separate the two crops. Results suggested that the mapped areas of soybean and corn agreed with official statistics at the municipal level. The resultant map in the crop year 2012 was evaluated using an independent reference data set, and the overall accuracy and Kappa coefficient were 87.2% and 0.804 respectively. As a result of mixed pixel effect at the 500 m resolution, classification results were biased depending on topography. In the flat, broad and highly-cropped areas, uncultivated lands were likely to be identified as soybean or corn, causing over-estimation of cropland area. By contrast, scattered crop fields in mountainous regions with dense natural vegetation tend to be overlooked. For future mapping efforts, it has great

Recognizing and reducing cognitive bias in clinical and forensic neurology.

Science.gov (United States)

Satya-Murti, Saty; Lockhart, Joseph

2015-10-01

In medicine, cognitive errors form the basis of bias in clinical practice. Several types of bias are common and pervasive, and may lead to inaccurate diagnosis or treatment. Forensic and clinical neurology, even when aided by current technologies, are still dependent on cognitive interpretations, and therefore prone to bias. This article discusses 4 common biases that can lead the clinician astray. They are confirmation bias (selective gathering of and neglect of contradictory evidence); base rate bias (ignoring or misusing prevailing base rate data); hindsight bias (oversimplification of past causation); and good old days bias (the tendency for patients to misremember and exaggerate their preinjury functioning). We briefly describe strategies adopted from the field of psychology that could minimize bias. While debiasing is not easy, reducing such errors requires awareness and acknowledgment of our susceptibility to these cognitive distortions.

Attentional Bias in Math Anxiety

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Orly eRubinsten

2015-10-01

Full Text Available Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety as well (i.e., a persistent negative reaction to math. Twenty seven participants (14 with high levels of math anxiety and 13 with low levels of math anxiety were presented with a novel computerized numerical version of the well established dot probe task. One of 6 types of prime stimuli, either math related or typically neutral, were presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks. Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in math anxiety. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words. These findings suggest that attentional bias is linked to unduly intense math anxiety symptoms.

Exchange bias in nearly perpendicularly coupled ferromagnetic/ferromagnetic system

International Nuclear Information System (INIS)

Bu, K.M.; Kwon, H.Y.; Oh, S.W.; Won, C.

2012-01-01

Exchange bias phenomena appear not only in ferromagnetic/antiferromagnetic systems but also in ferromagnetic/ferromagnetic systems in which two layers are nearly perpendicularly coupled. We investigated the origin of the symmetry-breaking mechanism and the relationship between the exchange bias and the system's energy parameters. We compared the results of computational Monte Carlo simulations with those of theoretical model calculation. We found that the exchange bias exhibited nonlinear behaviors, including sign reversal and singularities. These complicated behaviors were caused by two distinct magnetization processes depending on the interlayer coupling strength. The exchange bias reached a maximum at the transition between the two magnetization processes. - Highlights: ► Exchange bias phenomena are found in perpendicularly coupled F/F systems. ► Exchange bias exhibits nonlinear behaviors, including sign reversal and singularities. ► These complicated behaviors were caused by two distinct magnetization processes. ► Exchange bias reached a maximum at the transition between the two magnetization processes. ► We established an equation to maximize the exchange bias in perpendicularly coupled F/F system.

Detectability of migrating raptors and its effect on bias and precision of trend estimates

Directory of Open Access Journals (Sweden)

Eric G. Nolte

2016-12-01

Full Text Available Annual counts of migrating raptors at fixed observation points are a widespread practice, and changes in numbers counted over time, adjusted for survey effort, are commonly used as indices of trends in population size. Unmodeled year-to-year variation in detectability may introduce bias, reduce precision of trend estimates, and reduce power to detect trends. We conducted dependent double-observer surveys at the annual fall raptor migration count at Lucky Peak, Idaho, in 2009 and 2010 and applied Huggins closed-capture removal models and information-theoretic model selection to determine the relative importance of factors affecting detectability. The most parsimonious model included effects of observer team identity, distance, species, and day of the season. We then simulated 30 years of counts with heterogeneous individual detectability, a population decline (λ = 0.964, and unexplained random variation in the number of available birds. Imperfect detectability did not bias trend estimation, and increased the time required to achieve 80% power by less than 11%. Results suggested that availability is a greater source of variance in annual counts than detectability; thus, efforts to account for availability would improve the monitoring value of migration counts. According to our models, long-term trends in observer efficiency or migratory flight distance may introduce substantial bias to trend estimates. Estimating detectability with a novel count protocol like our double-observer method is just one potential means of controlling such effects. The traditional approach of modeling the effects of covariates and adjusting the index may also be effective if ancillary data is collected consistently.

Topographical mapping system for hazardous and radiological environments

International Nuclear Information System (INIS)

Armstrong, G.A.; Burks, B.L.; Bernacki, B.E.; Pardini, A.

1995-01-01

This report focuses on the results of the acceptance test of the Topographical Mapping System (TMS) delivered to the Hanford site. The TMS was tested for accuracy over the specified range of 45 feet. The TMS was also tested to ensure that the unit could be deployed through multiple risers and maintain accuracy and registration of the surface mapping data. In addition, the TMS was disassembled and reassembled and redeployed to test field replacement of modules that make up the sensor head that is deployed in the vapor space of Underground Storage Tanks such as those located at the Hanford site in southeastern Washington State. The results from these tests along with temperature testing on the complete system and radiation testing of selected susceptible components are covered in this report. The primary purpose of the TMS is to generate reliable and accurate three-dimensional maps of the internal surfaces of storage tank. One use for these mapping systems is in creating and maintaining a current map of the tank interior as input to a robotic ''world model'' that is used to test remediation strategies or plan robot trajectories. Another use is tracking the movement of the waste surface as it responds to expanding bubbles of trapped Gas. A third use of the TMS is to perform a volumetric analysis of the amount of waste removed from the tanks during remediation

Bias-correction in vector autoregressive models: A simulation study

DEFF Research Database (Denmark)

Engsted, Tom; Pedersen, Thomas Quistgaard

We analyze and compare the properties of various methods for bias-correcting parameter estimates in vector autoregressions. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study, we show that this simple...... and easy-to-use analytical bias formula compares very favorably to the more standard but also more computer intensive bootstrap bias-correction method, both in terms of bias and mean squared error. Both methods yield a notable improvement over both OLS and a recently proposed WLS estimator. We also...... of pushing an otherwise stationary model into the non-stationary region of the parameter space during the process of correcting for bias....

Short-Term Memory for Space and Time Flexibly Recruit Complementary Sensory-Biased Frontal Lobe Attention Networks.

Science.gov (United States)

Michalka, Samantha W; Kong, Lingqiang; Rosen, Maya L; Shinn-Cunningham, Barbara G; Somers, David C

2015-08-19

The frontal lobes control wide-ranging cognitive functions; however, functional subdivisions of human frontal cortex are only coarsely mapped. Here, functional magnetic resonance imaging reveals two distinct visual-biased attention regions in lateral frontal cortex, superior precentral sulcus (sPCS) and inferior precentral sulcus (iPCS), anatomically interdigitated with two auditory-biased attention regions, transverse gyrus intersecting precentral sulcus (tgPCS) and caudal inferior frontal sulcus (cIFS). Intrinsic functional connectivity analysis demonstrates that sPCS and iPCS fall within a broad visual-attention network, while tgPCS and cIFS fall within a broad auditory-attention network. Interestingly, we observe that spatial and temporal short-term memory (STM), respectively, recruit visual and auditory attention networks in the frontal lobe, independent of sensory modality. These findings not only demonstrate that both sensory modality and information domain influence frontal lobe functional organization, they also demonstrate that spatial processing co-localizes with visual processing and that temporal processing co-localizes with auditory processing in lateral frontal cortex. Copyright © 2015 Elsevier Inc. All rights reserved.

Short-term memory for space and time flexibly recruit complementary sensory-biased frontal lobe attention networks

Science.gov (United States)

Michalka, Samantha W.; Kong, Lingqiang; Rosen, Maya L.; Shinn-Cunningham, Barbara G.; Somers, David C.

2015-01-01

Summary The frontal lobes control wide-ranging cognitive functions; however, functional subdivisions of human frontal cortex are only coarsely mapped. Here, functional magnetic resonance imaging reveals two distinct visual-biased attention regions in lateral frontal cortex, superior precentral sulcus (sPCS) and inferior precentral sulcus (iPCS), anatomically interdigitated with two auditory-biased attention regions, transverse gyrus intersecting precentral sulcus (tgPCS) and caudal inferior frontal sulcus (cIFS). Intrinsic functional connectivity analysis demonstrates that sPCS and iPCS fall within a broad visual-attention network, while tgPCS and cIFS fall within a broad auditory-attention network. Interestingly, we observe that spatial and temporal short-term memory (STM), respectively, recruit visual and auditory attention networks in the frontal lobe, independent of sensory modality. These findings not only demonstrate that both sensory modality and information domain influence frontal lobe functional organization, they also demonstrate that spatial processing co-localizes with visual processing and that temporal processing co-localizes with auditory processing in lateral frontal cortex. PMID:26291168

Publication bias in dermatology systematic reviews and meta-analyses.

Science.gov (United States)

Atakpo, Paul; Vassar, Matt

2016-05-01

Systematic reviews and meta-analyses in dermatology provide high-level evidence for clinicians and policy makers that influence clinical decision making and treatment guidelines. One methodological problem with systematic reviews is the under representation of unpublished studies. This problem is due in part to publication bias. Omission of statistically non-significant data from meta-analyses may result in overestimation of treatment effect sizes which may lead to clinical consequences. Our goal was to assess whether systematic reviewers in dermatology evaluate and report publication bias. Further, we wanted to conduct our own evaluation of publication bias on meta-analyses that failed to do so. Our study considered systematic reviews and meta-analyses from ten dermatology journals from 2006 to 2016. A PubMed search was conducted, and all full-text articles that met our inclusion criteria were retrieved and coded by the primary author. 293 articles were included in our analysis. Additionally, we formally evaluated publication bias in meta-analyses that failed to do so using trim and fill and cumulative meta-analysis by precision methods. Publication bias was mentioned in 107 articles (36.5%) and was formally evaluated in 64 articles (21.8%). Visual inspection of a funnel plot was the most common method of evaluating publication bias. Publication bias was present in 45 articles (15.3%), not present in 57 articles (19.5%) and not determined in 191 articles (65.2%). Using the trim and fill method, 7 meta-analyses (33.33%) showed evidence of publication bias. Although the trim and fill method only found evidence of publication bias in 7 meta-analyses, the cumulative meta-analysis by precision method found evidence of publication bias in 15 meta-analyses (71.4%). Many of the reviews in our study did not mention or evaluate publication bias. Further, of the 42 articles that stated following PRISMA reporting guidelines, 19 (45.2%) evaluated for publication bias. In

Remote Sensing of Sub-Surface Suspended Sediment Concentration by Using the Range Bias of Green Surface Point of Airborne LiDAR Bathymetry

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Xinglei Zhao

2018-04-01

Full Text Available Suspended sediment concentrations (SSCs have been retrieved accurately and effectively through waveform methods by using green-pulse waveforms of airborne LiDAR bathymetry (ALB. However, the waveform data are commonly difficult to analyze. Thus, this paper proposes a 3D point-cloud method for remote sensing of SSCs in calm waters by using the range biases of green surface points of ALB. The near water surface penetrations (NWSPs of green lasers are calculated on the basis of the green and reference surface points. The range biases (ΔS are calculated by using the corresponding NWSPs and beam-scanning angles. In situ measured SSCs (C and range biases (ΔS are used to establish an empirical C-ΔS model at SSC sampling stations. The SSCs in calm waters are retrieved by using the established C-ΔS model. The proposed method is applied to a practical ALB measurement performed by Optech Coastal Zone Mapping and Imaging LiDAR. The standard deviations of the SSCs retrieved by the 3D point-cloud method are less than 20 mg/L.

SU-E-J-113: Effects of Deformable Registration On First-Order Texture Maps Calculated From Thoracic Lung CT Scans

International Nuclear Information System (INIS)

Smith, C; Cunliffe, A; Al-Hallaq, H; Armato, S

2015-01-01

Purpose: To determine the stability of eight first-order texture features following the deformable registration of serial computed tomography (CT) scans. Methods: CT scans at two different time points from 10 patients deemed to have no lung abnormalities by a radiologist were collected. Following lung segmentation using an in-house program, texture maps were calculated from 32×32-pixel regions of interest centered at every pixel in the lungs. The texture feature value of the ROI was assigned to the center pixel of the ROI in the corresponding location of the texture map. Pixels in the square ROI not contained within the segmented lung were not included in the calculation. To quantify the agreement between ROI texture features in corresponding pixels of the baseline and follow-up texture maps, the Fraunhofer MEVIS EMPIRE10 deformable registration algorithm was used to register the baseline and follow-up scans. Bland-Altman analysis was used to compare registered scan pairs by computing normalized bias (nBias), defined as the feature value change normalized to the mean feature value, and normalized range of agreement (nRoA), defined as the range spanned by the 95% limits of agreement normalized to the mean feature value. Results: Each patient’s scans contained between 6.8–15.4 million ROIs. All of the first-order features investigated were found to have an nBias value less than 0.04% and an nRoA less than 19%, indicating that the variability introduced by deformable registration was low. Conclusion: The eight first-order features investigated were found to be registration stable. Changes in CT texture maps could allow for temporal-spatial evaluation of the evolution of lung abnormalities relating to a variety of diseases on a patient-by-patient basis. SGA and HA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. Research reported in this publication was supported by the National Institute Of General

SU-E-J-113: Effects of Deformable Registration On First-Order Texture Maps Calculated From Thoracic Lung CT Scans

Energy Technology Data Exchange (ETDEWEB)

Smith, C; Cunliffe, A; Al-Hallaq, H; Armato, S [The University of Chicago, Chicago, IL (United States)

2015-06-15

Purpose: To determine the stability of eight first-order texture features following the deformable registration of serial computed tomography (CT) scans. Methods: CT scans at two different time points from 10 patients deemed to have no lung abnormalities by a radiologist were collected. Following lung segmentation using an in-house program, texture maps were calculated from 32×32-pixel regions of interest centered at every pixel in the lungs. The texture feature value of the ROI was assigned to the center pixel of the ROI in the corresponding location of the texture map. Pixels in the square ROI not contained within the segmented lung were not included in the calculation. To quantify the agreement between ROI texture features in corresponding pixels of the baseline and follow-up texture maps, the Fraunhofer MEVIS EMPIRE10 deformable registration algorithm was used to register the baseline and follow-up scans. Bland-Altman analysis was used to compare registered scan pairs by computing normalized bias (nBias), defined as the feature value change normalized to the mean feature value, and normalized range of agreement (nRoA), defined as the range spanned by the 95% limits of agreement normalized to the mean feature value. Results: Each patient’s scans contained between 6.8–15.4 million ROIs. All of the first-order features investigated were found to have an nBias value less than 0.04% and an nRoA less than 19%, indicating that the variability introduced by deformable registration was low. Conclusion: The eight first-order features investigated were found to be registration stable. Changes in CT texture maps could allow for temporal-spatial evaluation of the evolution of lung abnormalities relating to a variety of diseases on a patient-by-patient basis. SGA and HA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. Research reported in this publication was supported by the National Institute Of General

Human and animal evidence of potential transgenerational inheritance of health effects: An evidence map and state-of-the-science evaluation.

Science.gov (United States)

Walker, Vickie R; Boyles, Abee L; Pelch, Katherine E; Holmgren, Stephanie D; Shapiro, Andrew J; Blystone, Chad R; Devito, Michael J; Newbold, Retha R; Blain, Robyn; Hartman, Pamela; Thayer, Kristina A; Rooney, Andrew A

2018-06-01

An increasing number of reports suggest early life exposures result in adverse effects in offspring who were never directly exposed; this phenomenon is termed "transgenerational inheritance." Given concern for public health implications for potential effects of exposures transmitted to subsequent generations, it is critical to determine how widespread and robust this phenomenon is and to identify the range of exposures and possible outcomes. This scoping report examines the evidence for transgenerational inheritance associated with exposure to a wide range of stressors in humans and animals to identify areas of consistency, uncertainty, data gaps, and to evaluate general risk of bias issues for the transgenerational study design. A protocol was developed to collect and categorize the literature into a systematic evidence map for transgenerational inheritance by health effects, exposures, and evidence streams following the Office of Health Assessment and Translation (OHAT) approach for conducting literature-based health assessments. A PubMed search yielded 63,758 unique records from which 257 relevant studies were identified and categorized into a systematic evidence map by evidence streams (46 human and 211 animal), broad health effect categories, and exposures. Data extracted from the individual studies are available in the Health Assessment Workspace Collaborative (HAWC) program. There are relatively few bodies of evidence where multiple studies evaluated the same exposure and the same or similar outcomes. Studies evaluated for risk of bias generally had multiple issues in design or conduct. The evidence mapping illustrated that risk of bias, few studies, and heterogeneity in exposures and endpoints examined present serious limitations to available bodies of evidence for assessing transgenerational effects. Targeted research is suggested to addressed inconsistencies and risk of bias issues identified, and thereby establish more robust bodies of evidence to

Practical Bias Correction in Aerial Surveys of Large Mammals: Validation of Hybrid Double-Observer with Sightability Method against Known Abundance of Feral Horse (Equus caballus) Populations.

Science.gov (United States)

Lubow, Bruce C; Ransom, Jason I

2016-01-01

Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses (Equus caballus) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs.

Recent Advances in Attention Bias Modification for Substance Addictions

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Melvyn Weibin Zhang

2018-04-01

Full Text Available Research on attentional bias modification has increased since 2014. A recent meta-analysis demonstrates evidence for bias modification for substance disorders, including alcohol and tobacco use disorders. Several pharmacological trials have shown that pharmacological agents can attenuate and modify such attentional bias. The pharmacological trials that have appeared to date have produced mixed results, which has clinical implications. Developments in Internet and mobile technologies have transformed how attention bias modification is currently being achieved. There remains great potential for further research that examines the efficacy of technology-aided attention bias interventions.

A Bac Library and Paired-PCR Approach to Mapping and Completing the Genome Sequence of Sulfolobus Solfataricus P2

DEFF Research Database (Denmark)

She, Qunxin; Confalonieri, F.; Zivanovic, Y.

2000-01-01

The original strategy used in the Sulfolobus solfatnricus genome project was to sequence non overlapping, or minimally overlapping, cosmid or lambda inserts without constructing a physical map. However, after only about two thirds of the genome sequence was completed, this approach became counter......-productive because there was a high sequence bias in the cosmid and lambda libraries. Therefore, a new approach was devised for linking the sequenced regions which may be generally applicable. BAC libraries were constructed and terminal sequences of the clones were determined and used for both end mapping and PCR...

Giant exchange bias in MnPd/Co bilayers

International Nuclear Information System (INIS)

Nguyen Thanh Nam; Nguyen Phu Thuy; Nguyen Anh Tuan; Nguyen Nguyen Phuoc; Suzuki, Takao

2007-01-01

A systematic study of exchange bias in MnPd/Co bilayers has been carried out, where the dependences of exchange bias, unidirectional anisotropy constant and coercivity on the thicknesses of MnPd and Co layers were investigated. A huge unidirectional anisotropy constant, J K =2.5erg/cm 2 was observed, which is in reasonable agreement with the theoretical prediction based on the model by Meiklejohn and Bean. The angular dependences of exchange bias field and coercivity have also been examined showing that both exchange bias and coercivity follow 1/cosα rule